contents

 

front matter

preface

acknowledgments

about this book

about the author

about the cover illustration

Part 1. Deep learning fundamentals

  1   Designing modern machine learning

  1.1  A focus on adaptability

Computer vision leading the way

Beyond computer vision: NLP, NLU, structured data

  1.2  The evolution in machine learning approaches

Classical AI vs. narrow AI

Next steps in computer learning

  1.3  The benefits of design patterns

  2   Deep neural networks

  2.1  Neural network basics

Input layer

Deep neural networks

Feed-forward networks

Sequential API method

Functional API method

Input shape vs. input layer

Dense layer

Activation functions

Shorthand syntax

Improving accuracy with an optimizer

Feature detection