Syllabus

This syllabus is tentative and subject to change.

Date Links to the lecture pages Remarks and quick links
2/02 Introduction Slides: pdf.
2/04 Simple linear models Slides: pdf.
Scribe notes: Gelbart
Assignment: Homework #1, due 02/23.
2/09 R Tutorial (Sean Gerrish). Slides: pdf.
2/11 Cancelled
2/16 Review: linear algebra, probabilities Lecture notes: pdf pdf
Scribe notes: Valentino & Misener
2/18 Review: more probabilities Lecture notes: pdf
Scribe notes: Scott
2/23 Classification Slides: pdf
Scribe notes: NGuyen
Assignment: Homework #2, due 3/09 03/23.
2/25 Estimating probabilities Slides: pdf
Scribe notes: Persaud
3/02 Optimisation Slides: pdf
3/04 Clustering Slides: pdf
Scribe notes: Xiang & Yu.
3/09 Expectation-Maximization Slides: pdf
Scribe notes: Ali
Assignment: Homework #3, due 03/30.
3/11 Multilayer Networks Slides: pdf
Scribe notes: Harrison
SPRING BREAK
3/23 Exploratory methods: PCA Slides: pdf (part I)
Scribe notes:
3/25 Exploratory methods: CA, MCA Slides: pdf (parts II-IV)
Scribe notes: Tzeneva
Assignment: Homework #4, due 04/13.
3/30 Generalization and capacity control Slides: pdf
4/01 Support vector machines Slides: pdf
Scribe notes:
4/06 Information theory and decision trees Slides: pdf
Scribe notes:
4/08 Ensembles Slides: pdf
Scribe notes: Lee
4/13 Hidden Markov models Slides: pdf
Scribe notes: Kroll & Stewart
Deadline: Project proposal.
4/15 Graphical models Slides: pdf
Scribe notes:
4/20 Graph transducers Slides: pdf
Scribe notes: Chai
4/22 Feature engineering Slides: pdf
Scribe notes:
4/27 Natural language processing
and weak supervision
Slides: pdf
4/29 Final review
5/04 Poster session Deadline: Project posters.


See the lecture pages for pointers to readings, scribe notes, slides, etc.

 
syllabus.txt · Last modified: 2010/04/29 16:19 by lbottou
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