Summary

In this chapter, we saw how to find common, publicly available datasets that can be used to test various machine learning models. You learned how to load, process, and clean data, as well as how to apply common techniques to transform raw data into feature vectors that can be used as training examples for our models.

In the next chapter, you will learn the basics of recommender systems and explore how to create a recommendation model, use the model to make predictions, and evaluate the model.