In this chapter, we're going to focus on some advanced topics. We'll cover two topics: recommender systems and neural networks. We'll start with collaborative filtering, and then we'll look at integrating content-based similarities into collaborative filtering systems. We'll get into neural networks and transfer learning. Finally, we'll introduce the math and concept behind each of these, before getting into Python code.
We will cover the following topics:
- Recommended systems and an introduction to collaborative filtering
- Matrix factorization
- Content-based filtering
- Neural networks and deep learning
- Using transfer learning
