Recommender Systems: An Applied Approach using Deep Learning - VAE Collaborative Filtering

The video tutorial introduces the concept of autoencoders in recommender systems, focusing on how they learn non-linear representations of user-item matrices and reconstruct them using missing values. It explains the two main components: the encoder, which transforms user interactions into latent feature representations, and the decoder, which predicts user-item interaction probabilities. The course is designed to provide a foundational understanding of deep learning in recommender systems, with future videos covering strengths and limitations.

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