Deep Learning for Recommender Systems

Explore the cutting-edge applications of deep neural networks in recommender systems through this 30-minute conference talk. Delve into the current state-of-the-art collaborative filtering and content-based methods that leverage deep learning techniques to enhance recommendation accuracy. Discover why deep learning is considered the "next big thing" in recommender systems and learn about complex architectures, research directions, and the geometry of embedding spaces. Gain insights into autoencoder-based recommendations, RNN-based machine learning, and personalized session-based recommender systems. Understand how deep learning is revolutionizing various aspects of recommendation technology, from computer vision to natural language processing and speech recognition.

Intro
Recommender Systems
Why Deep Learning?
Complex Architectures
Research directions in DL-RecSys
Geometry of the Embedding Space
2c for Recommendations
Autoencoders for recommendation
RNN-based machine learning
Personalized Session-based RecSys