Difference between revisions of "Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2015"
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* Tues Sep 22. [[Class_meeting_for_10-605_Rocchio_and_On-line_Learning|Rocchio and TFIDF]] | * Tues Sep 22. [[Class_meeting_for_10-605_Rocchio_and_On-line_Learning|Rocchio and TFIDF]] | ||
* Thus Sep 24. [[Class meeting for 10-605 Similarity Joins|Fast KNN and similarity joins]] | * Thus Sep 24. [[Class meeting for 10-605 Similarity Joins|Fast KNN and similarity joins]] | ||
| − | * Tues Sep 29. [[Class meeting for 10-605 | + | |
| − | * Thus | + | * Tues Sep 29. [[Class meeting for 10-605 SGD and Hash Kernels|Scalable SGD and Hash Kernels]] |
| + | * Thus Oct 1. TBA | ||
''need to revise'' | ''need to revise'' | ||
| Line 22: | Line 23: | ||
== October == | == October == | ||
| − | * Tues Oct 6. [[Class meeting for 10-605 | + | * Tues Oct 6. [[Class meeting for 10-605 Parallel Perceptrons 1|Parallel Perceptrons 1]]. |
| − | * Thus Oct 8. [[Class meeting for 10-605 | + | * Thus Oct 8. [[Class meeting for 10-605 Parallel Perceptrons 2|Parallel Perceptrons 2]]. |
| − | * Tues Oct 13. | + | * Tues Oct 13. Parameter servers and AllReduce |
* Thus Oct 15. [[Class meeting for 10-605 SGD for MF|Matrix Factorization and SGD]] | * Thus Oct 15. [[Class meeting for 10-605 SGD for MF|Matrix Factorization and SGD]] | ||
* Tues Oct 20. TBA | * Tues Oct 20. TBA | ||
| − | * Thus Oct 22. | + | * Thus Oct 22. ''midterm exam'' |
| − | * Tues Oct 27. | + | * Tues Oct 27. [[Class meeting for 10-605 Randomized|Randomized Algorithms 1]] |
| − | * Thus Oct 29. | + | * Thus Oct 29. [[Class meeting for 10-605 Randomized|Randomized Algorithms 2]] |
== November == | == November == | ||
| − | * Tues Nov 3. [[Class meeting for 10-605 Subsample A Graph|Scalable PageRank] | + | * Tues Nov 3. [[Class meeting for 10-605 Subsample A Graph|Scalable PageRank]] |
* Thus Nov 5. [[Class meeting for 10-605 Subsampling Graphs|Subsampling a graph with RWR]] | * Thus Nov 5. [[Class meeting for 10-605 Subsampling Graphs|Subsampling a graph with RWR]] | ||
| − | * Tues Nov 10. | + | * Tues Nov 10. [[Class_meeting_for_10-605_SSL_on_Graphs|SSL on Graphs]] |
| − | * Thus Nov 12. | + | * Thus Nov 12. [[Class meeting for 10-605 GraphLab|Graph models for large-scale ML]] |
| − | * 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]] | * 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 | + | * Tues Nov 24. TBA |
* Thus Nov 26. ''Happy Thanksgiving!'' | * Thus Nov 26. ''Happy Thanksgiving!'' | ||
== December == | == December == | ||
| − | * Tues Dec 1. | + | * Tues Dec 1. [[Class meeting for 10-605 First-Order Logics|First-order logics]] |
| − | * Thus Dec 3. [[ | + | * Thus Dec 3. [[Class meeting for 10-605 Scalable FOL|Scalable First-order logics]] |
| − | * Tues Dec 8. [[Class meeting for 10-605 | + | * Tues Dec 8. [[Class meeting for 10-605 Spectral Clustering|Scalable spectral clustering techniques.]] |
* Thus Dec 10. In-class exam. | * Thus Dec 10. In-class exam. | ||
| Line 52: | Line 53: | ||
* [[Class meeting for 10-605 PIG|Workflows in PIG]] | * [[Class meeting for 10-605 PIG|Workflows in PIG]] | ||
| − | * | + | * |
* [[Class meeting for 10-605 Scalable FOL|Scalable First-order logics]] | * [[Class meeting for 10-605 Scalable FOL|Scalable First-order logics]] | ||
* [[Class meeting for 10-605 Parallel Similarity Joins|Scalable Similarity Joins]] | * [[Class meeting for 10-605 Parallel Similarity Joins|Scalable Similarity Joins]] | ||
Revision as of 17:09, 14 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. Scalable SGD and Hash Kernels
- Thus Oct 1. TBA
need to revise
October
- Tues Oct 6. Parallel Perceptrons 1.
- Thus Oct 8. Parallel Perceptrons 2.
- Tues Oct 13. Parameter servers and AllReduce
- Thus Oct 15. Matrix Factorization and SGD
- Tues Oct 20. TBA
- Thus Oct 22. midterm exam
- Tues Oct 27. Randomized Algorithms 1
- Thus Oct 29. Randomized Algorithms 2
November
- Tues Nov 3. Scalable PageRank
- Thus Nov 5. Subsampling a graph with RWR
- Tues Nov 10. SSL on Graphs
- Thus Nov 12. Graph models for large-scale ML
- 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. First-order logics
- Thus Dec 3. Scalable First-order logics
- Tues Dec 8. Scalable spectral clustering techniques.
- Thus Dec 10. In-class exam.
