Summary

In this chapter, we learned about recommendation systems. We learned about different kinds of recommendation systems such as collaborative filtering, content-based filtering, and hybrid systems. We used the Retailrocket dataset to create two models of our recommendation system, one with matrix factorization, and one using a neural network. We saw that the neural network model gave pretty good accuracy.

In the next chapter, we'll learn about object detection at large scale with distributed TensorFlow.