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?

Evaluate responses using AI:

OFF

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

Evaluate responses using AI:

OFF