Neural Networks and Convolutional Neural Networks Essential Training
Posted by Superadmin on May 11 2023 04:43:34

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


01_001.Welcome

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


01_002.What you should know

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


01_003.Using the exercise files

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


02_004.Neurons and artificial neurons

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


02_005.Gradient descent

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


02_006.The XOR challenge and solution

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


02_007.Neural networks

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


03_008.Activation functions

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


03_009.Backpropagation and hyperparameters

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


03_010.Neural network visualization

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_011.Understanding the components in Keras

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_012.Setting up a Microsoft account on Azure

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_013.Introduction to MNIST

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_014.Preprocessing the training data

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_015.Preprocessing the test data

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_016.Building the Keras model

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_017.Compiling the neural network model

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_018.Training the neural network model

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


04_019.Accuracy and evaluation of the neural network model

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


05_020.Convolutions

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


05_021.Zero padding and pooling

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


06_022.Preprocessing and loading of data

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


06_023.Creating and compiling the model

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


06_024.Training and evaluating the model

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


07_025.Enhancements to CNNs

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


07_026.Image augmentation in Keras

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


08_027.ImageNet challenge

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


08_028.Working with VGG16

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


09_029.Next steps

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files

Neural Networks and Convolutional Neural Networks Essential Training

Created by Jonathan Fernandes


Ex_Files_Neural_Networks_EssT.zip

Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes

1h 19m • COURSE
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning. In this hands-on course, instructor Jonathan Fernandes covers fundamental neural and convolutional neural network concepts. Jonathan begins by providing an introduction to the components of neural networks, discussing activation functions and backpropagation. He then looks at convolutional neural networks, explaining why they're particularly good at image recognition tasks. He also steps through how to build a neural network model using Keras. Plus, learn about VGG16, the history of the ImageNet challenge, and more.

Topics include:
Neurons and artificial neurons
Components of neural networks
Neural network visualization
Neural network implementation in Keras
Compiling and training a neural network model
Accuracy and evaluation of a neural network model
Convolutional neural networks in Keras
Enhancements to convolutional neural networks
Working with VGG16
      
Course Contents
01.Introduction 02.Introduction to Neural Networks 03.Components of Neural Networks 04.Neural Network Implementation in Keras 05.Convolutional Neural Networks 06.Convolutional Neural Networks in Keras 07.Enhancements to Convolutional Neural Networks (CNNs) 08.ImageNet 09.Conclusion Exercise Files