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?