Subject
3 entries
Clustering
Bookmarks
Models and Algorithms for Unlabelled Data
Vaibhav Verdhan's Manning book on unsupervised learning algorithms, covering clustering, dimensionality reduction, and anomaly detection with Python implementations on real-world datasets. Practical in orientation — stronger on applied case studies than mathematical rigor.
Programmatically Understanding the Expectation Maximization Algorithm
Nipun Batra's programmatic walkthrough of the Expectation Maximization algorithm — showing the E and M steps in code to build intuition for how EM converges. Makes the algorithm's alternating optimization structure tangible.
K-Means Clustering 86 Single Malt Scotch Whiskies
Clustering 86 single malt Scotch whiskies by flavor profile using k-means in R — a fun worked example that makes clustering tangible. Shows how to choose k and interpret results when the data has real-world meaning.