contents

 

  

      Front matter

preface

acknowledgments

about this book

about the author

about the cover illustration

  

Part 1. Getting started

  1 Introducing evolutionary deep learning

  1.1   What is evolutionary deep learning?

Introducing evolutionary computation

  1.2   The why and where of evolutionary deep learning

  1.3   The need for deep learning optimization

Optimizing the network architecture

  1.4   Automating optimization with automated machine learning

What is automated machine learning?

  1.5   Applications of evolutionary deep learning

Model selection: Weight search

Model architecture: Architecture optimization

Hyperparameter tuning/optimization

Validation and loss function optimization

Neuroevolution of augmenting topologies