AI

This course covers unsupervised learning, the branch of machine learning that finds patterns in data without any labeled answers to learn from. You'll learn k-means clustering in practical detail, get a conceptual tour of dimensionality reduction and anomaly detection, and confront why evaluating unsupervised models is fundamentally harder than evaluating supervised ones. This is part 2 of the Applied Machine Learning track, and assumes you already understand supervised learning from part 1.