Difference between revisions of "Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2015"
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* Thus Nov 12. TBA | * Thus Nov 12. TBA | ||
* Tues Nov 17. [[Class meeting for 10-605 LDA 1|Sparse sampling and parallelization for LDA]] | * Tues Nov 17. [[Class meeting for 10-605 LDA 1|Sparse sampling and parallelization for LDA]] | ||
| + | * Thus Nov 19. [[Class meeting for 10-605 2013 LDA 2|Speeding up LDA-like models: All-reduce and other tricks]] | ||
| + | * Tues Nov 24. TBA | ||
| + | * Thus Nov 26. ''Happy Thanksgiving!'' | ||
| + | == December == | ||
| − | * | + | * Tues Dec 1. TBA. |
| − | + | * Thus Dec 3. [[Class_meeting_for_10-605_SSL_on_Graphs|SSL on Graphs]] | |
| − | + | * Tues Dec 8. [[Class meeting for 10-605 GraphLab|Graph models for large-scale ML]] | |
| − | * Thus | + | * Thus Dec 10. In-class exam. |
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== Topics covered in previous years but not in 2015 == | == Topics covered in previous years but not in 2015 == | ||
Revision as of 17:34, 7 July 2015
This is the syllabus for Machine Learning with Large Datasets 10-605 in Fall 2015.
Notes:
- The assignments posted are drafts based on the assignments from spring 2015, and will be modified over the course of the semester - some may be changed substantially.
- Lecture notes and/or slides will be (re)posted around the time of the lectures.
Contents
September
- Tues Sep 1. Overview of course, cost of various operations, asymptotic analysis.
- Thus Sep 3. Review of probabilities, joint distributions and naive Bayes
- Tues Sep 8. Streaming algorithms and Naive Bayes; The stream-and-sort design pattern; Naive Bayes for large feature sets.
- Thus Sep 10. Messages, records and workflows; Phrase finding.
- Tues Sep 15. Hadoop and Map-Reduce
- Thus Sep 17. PIG and Other Workflow Systems for Hadoop
- Tues Sep 22. Rocchio and TFIDF
- Thus Sep 24. Fast KNN and similarity joins
- Tues Sep 29. Parallel Perceptrons 1.
- Thus Sep 30. Parallel Perceptrons 2.
need to revise
October
- Tues Oct 6. Scalable SGD and Hash Kernels
- Thus Oct 8. Randomized Algorithms 1
- Tues Oct 13. Randomized Algorithms 2
- Thus Oct 15. Matrix Factorization and SGD
- Tues Oct 20. TBA
- Thus Oct 22. TBA
- Tues Oct 27. TBA
- Thus Oct 29. TBA
November
- Tues Nov 3. Scalable PageRank PDF handout
- Thus Nov 5. Subsampling a graph with RWR
- Tues Nov 10. TBA
- Thus Nov 12. TBA
- Tues Nov 17. Sparse sampling and parallelization for LDA
- Thus Nov 19. Speeding up LDA-like models: All-reduce and other tricks
- Tues Nov 24. TBA
- Thus Nov 26. Happy Thanksgiving!
December
- Tues Dec 1. TBA.
- Thus Dec 3. SSL on Graphs
- Tues Dec 8. Graph models for large-scale ML
- Thus Dec 10. In-class exam.
