Building Recommender systems with Gaussian Mixture Model
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Create recommender systems using the Gaussian Mixture Model (GMM). Learn how to apply unsupervised machine learning algorithms to generate personalized recommendations based on user preferences and behavior in areas like e-commerce and media.
At a Glance
Building Recommender systems, creating anomaly detection algorithm or performing customer segmentation are all very complicated but yet common tasks. Gaussian Mixture Model is a powerful probabilistic algorithm that can be a great tool to perform all of those tasks and more. In this guided project, you will learn how to identify complex patterns, clusters, and subgroups in your datasets by using GMMs.
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