5—Collaborative filtering; Inside the training loop
You will learn about collaborative filtering through the example of making movie recommendations, and talk about key developments that occurred during the Netflix prize.
We will dig into some lower level details of deep learning: what happens inside the training loop, how optimizers like momentum and Adam work, and regularization using weight decay. You will learn how to think spatially about math concepts like the ‘chain rule’, ‘jacobian’, and ‘hessian’.
Click here for links, notes, and discussion of this lesson.