Deep-Learning-with-PyTorch

Using PyTorch
to fight cancer
This chapter covers
• Breaking a large problem into smaller, easier ones
• Exploring the constraints of an intricate deep
learning problem, and deciding on a structure
and approach
• Downloading the training data
We have two main goals for this chapter. We’ll start by covering the overall plan for
part 2 of the book so that we have a solid idea of the larger scope the following individual
chapters will be building toward. In chapter 10, we will begin to build out the
data-parsing and data-manipulation routines that will produce data to be consumed
in chapter 11 while training our first model. In order to do what’s needed
for those upcoming chapters well, we’ll also use this chapter to cover some of the
context in which our project will be operating: we’ll go over data formats, data
sources, and exploring the constraints that our problem domain places on us. Get
used to performing these tasks, since you’ll have to do them for any serious deep
learning project!
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