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1
Intro
2
Recommender Systems
3
Why Deep Learning?
4
Complex Architectures
5
Research directions in DL-RecSys
6
Geometry of the Embedding Space
7
2c for Recommendations
8
Autoencoders for recommendation
9
RNN-based machine learning
10
Personalized Session-based RecSys
Description:
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.

Deep Learning for Recommender Systems

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