. Lecture 7. Part 2. Clustering. Theory and practice

Here we overview the problem of clustering, why it’s so different from supervised learning problems, how to select the number of clusters. We discuss main approaches to perform clustering: k-Means, hierarchical clustering, DBSCAN. Then, some applications with Sklearn. Slides - Notebooks - Main site - Kaggle Dataset - GitHub repo -