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This lecture covers the applications of Gaussian Mixture Models (GMM) in recommender systems, focusing on topics such as structure from motion (SfM), simultaneous localization and mapping (SLAM), and examples from real-world applications like the Roomba robot. The instructor discusses the use of GMM for image credit and its role in surfacing personalized recommendations.