We learned that sometimes we can get rid of all the features using feature selection methods. We also saw that in some cases this is not enough, and we have to employ feature extraction methods that reveal the real and the lower-dimensional structure in our data, hoping that the model has an easier game with it.

We have only scratched the surface of the huge body of available dimensionality reduction methods. Still, we hope that we have got you interested in this whole field, as there are lots of other methods waiting for you to pick up. At the end, feature selection and extraction is an art, just like choosing the right learning method or training model.

The next chapter covers the use of Jug, a little Python framework to manage computations in a way that takes advantage of multiple cores or multiple machines. We will also learn about AWS – the Amazon cloud.