Understanding the components in Keras

Contents

• Introduction Introduction

  • Welcome

    41s
  • What you should know

    47s
  • Using the exercise files

    20s
• 1. Introduction to Neural Networks 1. Introduction to Neural Networks

  • Neurons and artificial neurons

    4m 31s
  • Gradient descent

    3m 34s
  • The XOR challenge and solution

    2m 18s
  • Neural networks

    3m 11s
• 2. Components of Neural Networks 2. Components of Neural Networks

  • Activation functions

    3m 1s
  • Backpropagation and hyperparameters

    1m 20s
  • Neural network visualization

    3m 49s
• 3. Neural Network Implementation in Keras 3. Neural Network Implementation in Keras

  • Understanding the components in Keras

    2m 12s
  • Setting up a Microsoft account on Azure

    1m 57s
  • Introduction to MNIST

    5m 33s
  • Preprocessing the training data

    4m 38s
  • Preprocessing the test data

    1m 58s
  • Building the Keras model

    2m 23s
  • Compiling the neural network model

    2m 18s
  • Training the neural network model

    1m 27s
  • Accuracy and evaluation of the neural network model

    2m 4s
• 4. Convolutional Neural Networks 4. Convolutional Neural Networks

  • Convolutions

    1m 22s
  • Zero padding and pooling

    5m 12s
• 5. Convolutional Neural Networks in Keras 5. Convolutional Neural Networks in Keras

  • Preprocessing and loading of data

    2m
  • Creating and compiling the model

    5m 16s
  • Training and evaluating the model

    2m 8s
• 6. Enhancements to Convolutional Neural Networks (CNNs) 6. Enhancements to Convolutional Neural Networks (CNNs)

  • Enhancements to CNNs

    1m 32s
  • Image augmentation in Keras

    3m 45s
• 7. ImageNet 7. ImageNet

  • ImageNet challenge

    2m 54s
  • Working with VGG16

    6m 14s
• Conclusion Conclusion

  • Next steps

    51s