Deep Learning for Coders with fastai and PyTorch

Chapter 1. Your Deep Learning Journey

Hello, and thank you for letting us join you on your deep learning journey, however far along that you may be! In this chapter, we will tell you a little bit more about what to expect in this book, introduce the key concepts behind deep learning, and train our first models on different tasks. It doesn’t matter if you don’t come from a technical or a mathematical background (though it’s OK if you do too!); we wrote this book to make deep learning accessible to as many people as possible.

Deep Learning Is for Everyone

A lot of people assume that you need all kinds of hard-to-find stuff to get great results with deep learning, but as you’ll see in this book, those people are wrong. Table 1-1 lists a few things you absolutely don’t need for world-class deep learning.

Table 1-1. What you don’t need for deep learning

Myth (don’t need)	Truth
Lots of math	High school math is sufficient.
Lots of data	We’ve seen record-breaking results with <50 items of data.
Lots of expensive computers	You can get what you need for state-of-the-art work for free.

Deep learning is a computer technique to extract and transform data—with use cases ranging from human speech recognition to animal imagery classification—by using multiple layers of neural networks. Each of these layers takes its inputs from previous layers and progressively refines them. The layers are trained by algorithms that minimize their errors and improve their accuracy. In this way, ...