Dimensionality Reduction | ML-005 Lecture 14 | Stanford University | Andrew Ng 

Contents:
Motivation 1 - Data Compression,
Motivation 2 - Visualization,
Principal Component Analysis - Problem Formulation,
Principal Component Analysis Algorithm,
Choosing the number of Principal Components,
Reconstruction from Compressed Representation,
Advice for Applying PCA.