Even for people comfortable with using them, neural networks can seem like a big black box. On top of that, the little bit of randomness within them just makes their inner workings that much more mysterious.
In this chapter, we're going to start exploring TDD-ing machine learning algorithms by building a very simple neural network using TDD. Then we will use this as an opportunity to more deeply understand how they work.
In this chapter, we will cover the following topics:
Building the simplest perceptron possible
Using a spreadsheet to develop simple use cases we can test to and reproduce
Using TDD to develop our first machine-learning algorithm
Testing with datasets
You will need some sort of spreadsheet program to follow along with this chapter. Microsoft Excel, Libre Office, or Google Docs are completely fine.