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DEMO - Pandas for Predictive Analysis using scikit learn
DEMO - Pandas for Predictive Analysis using scikit learnAnalytics Courses |
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| Superadmin | 01.01.70 | 425 | No Rating | |
| Description | ||||
| What You Will Learn Learn to read different kinds of data into Pandas Dataframes for data analysis. Discover how to manipulate, transform and apply formulas on the data imported into the pandas dataframes See how to analyze and visualize different kinds of data using Pandas, to gain real world insights. Get to know how to use Pandas to make predictions using Machine Learning and scikit-learn Work with Big Data using Pandas, and get useful information for your business decisions Practice data analysis with quantitative financial data and see how to model time-series data, perform algorithmic trading Take your Pandas to the next level by learning advanced techniques. Get to know how to take out transformed data out of Pandas dataframes and into the formats your application expects. Harish Garg is a Data Analyst, author, and Software Developer who is really passionate about Data Science and the Python programming language. He is a graduate from Udacity's Data Analyst Nanodegree program. He has 17 years of industry experience, which includes data analysis using Python, developing and testing enterprise and consumer software, managing projects and software teams, and creating training material and tutorials. Harish also worked for 11 years for Intel Security (previously McAfee, Inc.). He regularly contributes articles and tutorials on data analysis and Python. He is also active in the open data community and is a contributing member of the Data4Democracy open data initiative. He has written data analysis pieces for think tan takshashila. Who is the target audience? If you are a budding data scientist looking to learn the popular pandas library, or a Python developer looking to step into the world of data analysis, this video is the ideal resource you need to get started. Table of Contents SETTING UP SCIKIT-LEARN AND TRAINING YOUR FIRST ML MODEL The Course Overview Setting Up scikit-learn for Machine Learning Preprocessing Your Data to Make It Ready for Training a Model Training and Running the Classification Model Getting Your Own Data Ready for Machine Learning CHOOSING AND EVALUATING BEST ML MODELS Evaluating a Machine Learning Model Selecting Best Features for Training the Model Tuning Feature Performance TRYING OUT SOME DIFFERENT SCIKIT-LEARN ALGORITHMS Using Naive Bayes Classification Algorithm Building Models Using Support Vector Machine Using Decision Tree Classifiers PREDICT SENTIMENTS BASED ON TEXT Making Your Bag of Words Ready Building and Training a Model Making Predictions | ||||
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