Table of Contents

 

Copyright

Brief Table of Contents

Table of Contents

Preface

Acknowledgments

About this book

About the author

Chapter 1. Introducing deep learning: why you should learn it

Welcome to Grokking Deep Learning

You’re about to learn some of the most valuable skills of the century!

Why you should learn deep learning

It’s a powerful tool for the incremental automation of intelligence

Deep learning has the potential for significant automation of skilled labor

It’s fun and creative. You’ll discover much about what it is to be human by trying to simulate intelligence and creativity

Will this be difficult to learn?

How hard will you have to work before there’s a “fun” payoff?

Why you should read this book

It has a uniquely low barrier to entry

It will help you understand what’s inside a framework (Torch, TensorFlow, and so on)

All math-related material will be backed by intuitive analogies

Everything after the introduction chapters is “project” based

What you need to get started

Install Jupyter Notebook and the NumPy Python library

Pass high school mathematics

Find a personal problem you’re interested in

You’ll probably need some Python knowledge

Python is my teaching library of choice, but I’ll provide a few others online

How much coding experience should you have?

Summary

Chapter 2. Fundamental concepts: how do machines learn?

What is deep learning?

Deep learning is a subset of methods for machine learning

What is machine learning?