Table of Contents

 

Copyright

Brief Table of Contents

Table of Contents

Preface

Acknowledgments

About This Book

About the Author

About the Cover

1. Your machine-learning rig

Chapter 1. A machine-learning odyssey

1.1. Machine-learning fundamentals

1.1.1. Parameters

1.1.2. Learning and inference

1.2. Data representation and features

1.3. Distance metrics

1.4. Types of learning

1.4.1. Supervised learning

1.4.2. Unsupervised learning

1.4.3. Reinforcement learning

1.5. TensorFlow

1.6. Overview of future chapters

1.7. Summary

Chapter 2. TensorFlow essentials

2.1. Ensuring that TensorFlow works

2.2. Representing tensors

2.3. Creating operators

2.4. Executing operators with sessions

2.4.1. Understanding code as a graph

2.4.2. Setting session configurations

2.5. Writing code in Jupyter

2.6. Using variables

2.7. Saving and loading variables

2.8. Visualizing data using TensorBoard

2.8.1. Implementing a moving average