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Lecture
Unsupervised Learning: Representation & Generation
Description
This lecture focuses on unsupervised learning, where systems learn without labels. It covers how to create meaningful internal representations for data examples, reflecting their semantic structure. The main directions in unsupervised learning are representation learning and density estimation & generative models.
Official source
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