Recommender Systems: An Applied Approach using Deep Learning - Overview

This module covers the application of deep learning in recommender systems. It begins with an overview of deep learning methodologies, followed by a discussion on the benefits and challenges of using deep learning models. The module then explores recommendation inference and a generic deep learning-based recommendation approach. It introduces neutral collaborative filtering and variational autoencoders for collaborative filtering. Finally, the module concludes with the development of a deep learning recommendation system project.

What is the role of variational autoencoders in collaborative filtering?

Describe the project that will be developed in the next module regarding deep learning recommendation systems.