That was a tough ride—we covered preprocessing over clustering and a solution that could convert noisy text into a meaningful concise vector representation, which we could cluster. If we look at what we had to do to finally be able to cluster, it was more than half of the overall task. But on the way, we learned quite a bit about text processing and how simple counting can get you very far with noisy real-world data.
This ride has been made much smoother, though, because of scikit and its powerful packages. And there is more to explore. In this chapter, we were scratching the surface of its capabilities. In Chapter 7, Recommendations, we will build a recommendation system, and we will see more of its power.
