Intro to Deep Learning 2018 - Lesson 5

Prerequisites:
This 7-week course is designed for anyone with at least a year of coding experience, and some memory of high-school math. You will start with step one—learning how to get a GPU server online suitable for deep learning—and go all the way through to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems. There are around 20 hours of lessons, and you should plan to spend around 10 hours a week for 7 weeks to complete the material. The course is based on lessons recorded during the first certificate course at The Data Institute at USF.

TODAYS LESSON:

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’.