Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part4 - Advanced Statistical Methods in Python
Posted by Superadmin on November 13 2019 00:17:13

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


01.1. Introduction to Regression Analysis


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


01.2. 2. Introduction to Regression Analysis.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.1. The Linear Regression Model


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.2. The Linear Regression Model.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.3. Correlation vs Regression


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.4. Correlation vs Regression.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.5. Geometrical Representation of the Linear Regression Model


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.6. Python Packages Installation


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.7. First Regression in Python


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.7.1 Simple linear regression - Lecture.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.7.2 Simple linear regression - Exercise.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.8. First Regression in Python Exercise.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.8.1 Simple Linear Regression Exercise.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.9. Using Seaborn for Graphs


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.10. How to Interpret the Regression Table


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.11. Decomposition of Variability


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.12. Decomposition of Variability.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.13. What is the OLS


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.14. R-Squared


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


02.15. R-Squared.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.1. Multiple Linear Regression


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.2. Adjusted R-Squared


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.2.1 Multiple linear regression - Lecture.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.3. Adjusted R-Squared.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.4. Multiple Linear Regression Exercise.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.4.1 Multiple Linear Regression Exercise.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.5. Test for Significance of the Model (F-Test)


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.6. OLS Assumptions


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.7. OLS Assumptions.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.8. A1 Linearity


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.9. A1 Linearity.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.9. Understanding Line Continuation


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.10. A2 No Endogeneity


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.11. A2 No Endogeneity.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.12. A3 Normality and Homoscedasticity


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.13. A4 No Autocorrelation


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.14. A4 No autocorrelation.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.15. A5 No Multicollinearity


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.16. A5 No Multicollinearity.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.17. Dealing with Categorical Data - Dummy Variables


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.17.1 Dummies - Lecture.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.18. Dealing with Categorical Data - Dummy Variabless.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.18.1 Dummy variables Exercise.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.19. Making Predictions with the Linear Regression


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


03.19.1 Making predictions - Lecture.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.1. Introduction to Logistic Regression


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.2. A Simple Example in Python


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.2.1 Simple logistic regression example.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.3. Logistic vs Logit Function


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.4. Building a Logistic Regression


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.4.1 Building a logistic regression.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.5. An Invaluable Coding Tip


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.6. Understanding Logistic Regression Tables


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.7. What do the Odds Actually Mean


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.8. Binary Predictors in a Logistic Regression


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.8.1 Binary predictors.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.9. Calculating the Accuracy of the Model


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.9.1 Accuracy.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.10. Underfitting and Overfitting


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.11. Testing the Model


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


04.11.1 Test dataset.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


05.1. Introduction to Cluster Analysis


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


05.2. Some Examples of Clusters


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


05.3. Difference between Classification and Clustering


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


05.4. Math Prerequisites


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.1. K-Means Clustering


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.2. A Simple Example of Clustering


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.2.1 Country clusters.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.3. Clustering Categorical Data


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.3.1 Clustering categorical data.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.4. How to Choose the Number of Clusters


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.4.1 Selecting the number of clusters.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.5. Pros and Cons of K-Means Clustering


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.6. To Standardize or to not Standardize


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.7. Relationship between Clustering and Regression


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.8. Market Segmentation with Cluster Analysis (Part 1)


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.8.1 Market segmentation example.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.9. Market Segmentation with Cluster Analysis (Part 2)


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.9.1 Market segmentation example (Part 2).html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


06.10. How is Clustering Useful


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


07.1. Types of Clustering


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


07.2. Dendrogram


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


07.3. Heatmaps


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering

Udemy The Data Science Course 2018: Complete Data Science Bootcamp Part 4 Advanced Statistical Methods in Python

with Iliya


07.3.1 Heatmaps.html


The Data Science Course 2019: Complete Data Science Bootcamp
Complete Data Science Training: Mathematics, Statistics, Python, Advanced Statistics in Python, Machine & Deep Learning

What you'll learn::
  • The course provides the entire toolbox you need to become a data scientist
  • Impress interviewers by showing an understanding of the data science field
  • Understand the mathematics behind Machine Learning (an absolute must which other courses don’t teach!)
  • Perform linear and logistic regressions in Python
  • Be able to create Machine Learning algorithms in Python, using NumPy, statsmodels and scikit-learn
  • Use state-of-the-art Deep Learning frameworks such as Google’s TensorFlowDevelop a business intuition while coding and solving tasks with big data
  • Improve Machine Learning algorithms by studying underfitting, overfitting, training, validation, n-fold cross validation, testing, and how hyperparameters could improve performance
  • Fill up your resume with in demand data science skills: Statistical analysis, Python programming with NumPy, pandas, matplotlib, and Seaborn, Advanced statistical analysis, Tableau, Machine Learning with stats models and scikit-learn, Deep learning with TensorFlow
  • Learn how to pre-process data
  • Start coding in Python and learn how to use it for statistical analysis
  • Carry out cluster and factor analysis
  • Apply your skills to real-life business cases
  • Unfold the power of deep neural networks
  • Warm up your fingers as you will be eager to apply everything you have learned here to more and more real-life situations
      
Course Contents
01. Introduction to Regression Analysis 02. Advanced Statistical Methods - Linear regression 03. Advanced Statistical Methods - Multiple Linear Regression 04. Advanced Statistical Methods - Logistic Regression 05. Advanced Statistical Methods - Cluster Analysis 06. Python - Python Functions 07. Advanced Statistical Methods - Other Types of Clustering