This lecture covers the concept of unsupervised learning, focusing on movie recommendation systems. The instructor explains the process of finding relevant descriptions for each movie, using singular value decomposition (SVD) on the movie-user matrix. The lecture discusses how to choose the appropriate number of features (k) and the importance of the singular values in the recommendation process.
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