Lectures:

Lecture 1: Course Logistics/Dimensionality Reduction

Lecture 2: Singular Value Decomposition

Lecture 3: SVD, PCA, HITS, Markov Chain

Lecture 4: Markov Chain & Pagerank

Lecture 5: Clustering

Lecture 6: Clustering contd. 

Lecture 7: Spectral Clustering

Lecture 8: Similarity Queries

Lecture 9: Locality Sensitive Hashing

Lecture 10: Randomized Numerical Linear Algebra

Lecture 11: Data Streaming

Lecture 12: Count Distinct and Heavy Hitters

Lecture 13: Count-Min Sketch

Lecture 14: Online Learning

Lecture 15: Classifiers

Lecture 16: Optimization

Lecture 17: (Stochastic) Gradient Descent