# Lectures

- Lecture 1, Thursday Jan 28: course introduction, beginning of dimensionality reduction.
- Lecture 2, Tuesday Feb 2: Dimensionality reduction, Linear projection, PCA.
- Lecture 3, Thursday Feb 4: PCA. Additional lecture notes [notes] Smiley faces example with code (badly commented) [zip]
- Lecture 4, Tuesday Feb 9: Canonical Correlation Analysis: CCA
- Lecture 5, Thursday Feb 11: Random Projections Random Projections
- Lecture 6, Thursday Feb 18: Compressed Sensing CS
- Lecture 7, Tuesday Feb 23: Non-Linear Projection Nonlin Proj
- Lecture 8, Thursday Feb 25: Clustering Clustering
- Lecture 9, Tuesday March 1st: K-means and Single-link Clustering kmeansslink
- Lecture 10, Thursday March 3rd: Single-link Clustering and Spectral Clustering linkspec
- Lecture 11, Tuesday March 8th: Spectral Clustering spectral
- Lecture 12, Thursday March 10th: Clustering clustering apple doesnt fall far from the tree code snippet
- Lecture 13, Tuesday March 15th: Probabilistic Modelling, MLE Vs MAP Vs Bayesian, Latent Variables probmodel
- Lecture 14, Thursday March 17th: Latent Variables, EM Algorithm em
- Lecture 15, Tuesday March 22nd: EM Algorithm for GMM and Why EM works emforGMM
- Lecture 16, Thursday March 24th: EM Algorithm for Mixture Models emformm
- Lecture 17, Tuesday April 5th: Latnt Dirchlet Allocation and Intro to Graphical Models
LDA
- Lecture 18, Thursday April 7th: Graphical Models
GModels
- Lecture 19, Tuesday April 12th: Graphical Models
GModels
- Lecture 20, Thursday April 15th: Graphical Models: Message Passing
Infer
- Lecture 21, Tuesday April 19th: Graphical Models: Message Passing
Infer
- Lecture 22, Thursday April 21st: Graphical Models: Message Passing for trees, EM for learning
MP
- Lecture 23, Tuesday April 26th: Graphical Models: Inference cont., EM for learning
Inference and EM
- Lecture 24, Thursday April 28th: Graphical Models: Approximate Inference
Approx Inference
- Lecture 25, Tuesday May 3rd: Graphical Models: Approximate Inference
Approx Inference
- Lecture 26, Thursday May 5th: Wrapping up!
summary
- Lecture 27, Tuesday May 10th: Last LEcture
end