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Unsupervised learning is a category of machine learning algorithms that use unlabeled data and no prior training. Many algorithms fall into this category. This class will cover the more popular ones of K-Means, DBSCAN and Hierarchical Clustering. These algorithms can cluster data into groups. Some algorithms allow the user to decide how many groups that form, while other algorithms decide for the user. The course has weekly coding labs and ends with a capstone project. This allows students to demonstrate their understanding of the algorithms.
