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Artificial Intelligence, Machine Learning, and Deep Learning

Frontmatter

CONTENTS

Preface

Chapter 1: Introduction to AI

Chapter 2: Introduction to Machine Learning

Chapter 3: Classifiers in Machine Learning

Chapter 4: Deep Learning Introduction

Chapter 5: Deep Learning: RNNs and LSTMs

Chapter 6: NLP and Reinforcement Learning

Appendix A: Introduction to Keras

Appendix B: Introduction to TF 2

Appendix C: Introduction to Pandas

Index

AIMLDLdisc.zip

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and auto encoders. Keras-based code samples are included to supplement the theoretical discussion. In addition, this book contains appendices for Keras, TensorFlow 2, and Pandas.

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine...

Format

Artificial Intelligence, Machine Learning, and Deep Learning

Oswald Campesato

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