Second edition notebooks

These are the notebooks for the second edition of the book, originally published in 2021. These notebooks use tf.keras with TensorFlow 2.16.

Table of contents

• Chapter 2: The mathematical building blocks of neural networks

• Chapter 3: Introduction to Keras and TensorFlow

• Chapter 4: Getting started with neural networks: classification and regression

• Chapter 5: Fundamentals of machine learning

• Chapter 7: Working with Keras: a deep dive

• Chapter 8: Introduction to deep learning for computer vision

• Chapter 9: Advanced deep learning for computer vision

  • Part 1: Image segmentation

  • Part 2: Modern convnet architecture patterns

  • Part 3: Interpreting what convnets learn

• Chapter 10: Deep learning for timeseries

• Chapter 11: Deep learning for text

  • Part 1: Introduction

  • Part 2: Sequence models

  • Part 3: Transformer

  • Part 4: Sequence-to-sequence learning

• Chapter 12: Generative deep learning

  • Part 1: Text generation

  • Part 2: Deep Dream

  • Part 3: Neural style transfer

  • Part 4: Variational autoencoders

  • Part 5: Generative adversarial networks

• Chapter 13: Best practices for the real world

• Chapter 14: Conclusions