Lectures:

Lecture 1: Course logistics+Intro to SVD

Lecture 2: Singular Value Decomposition (Annotated)

Lecture 3: SVD, PCA and Applications (Annotated) 

Lecture 4: Markov Chain and Pagerank (Annotated)

Lecture 5: Clustering (Annotated)

Lecture 6: More on Clustering (Annotated)

Lecture 7: Spectral Clustering (Annotated)

Lecture 8: Similarity Queries (Annotated)

Lecture 9: Locality Sensitive Hashing(Annotated)

Lecture 10: Data Streaming (Annotated) + Probability Basics 

Lecture 11:  Data Streaming (Annotated)  

Lecture 12 & 13 : Data streaming: Count Distinct and Heavy Hitters  

Lecture 14: Data Streaming and Online Learning

 Lecture 15: Perceptron

 Lecture 16: SVM

 Lecture 17: Optimization

 Lecture 18: Gradient Descent 

Lecture 19: Stochastic Gradient Descent