To do

  • Watch Andrew Ng lectures 13:
    • Unsupervised learning intro
    • K-Means Algorithm
    • Optimization objective
    • Random initialization
    • Choosing the number of clusters

Done

  • Above and including lectures 14-1, 14-2, and 14-3
    • Motivation I - Data Compression
    • Motivation II - Visualization
    • Principle Component Analysis Problem Formulation