Difference between revisions of "Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2015"
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* 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. | * 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. | * Lecture notes and/or slides will be (re)posted around the time of the lectures. | ||
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* Tues Sep 1. [[Class meeting for 10-605 Overview|Overview of course, cost of various operations, asymptotic analysis.]] | * Tues Sep 1. [[Class meeting for 10-605 Overview|Overview of course, cost of various operations, asymptotic analysis.]] | ||
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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]] | ||
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* Tues Sep 29. [[Class meeting for 10-605 SGD and Hash Kernels|Scalable SGD and Hash Kernels]] | * Tues Sep 29. [[Class meeting for 10-605 SGD and Hash Kernels|Scalable SGD and Hash Kernels]] | ||
* Thus Oct 1. TBA | * Thus Oct 1. TBA | ||
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* Tues Oct 6. [[Class meeting for 10-605 Parallel Perceptrons 1|Parallel Perceptrons 1]]. | * Tues Oct 6. [[Class meeting for 10-605 Parallel Perceptrons 1|Parallel Perceptrons 1]]. | ||
* Thus Oct 8. [[Class meeting for 10-605 Parallel Perceptrons 2|Parallel Perceptrons 2]]. | * Thus Oct 8. [[Class meeting for 10-605 Parallel Perceptrons 2|Parallel Perceptrons 2]]. | ||
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* Tues Oct 20. TBA | * Tues Oct 20. TBA | ||
* Thus Oct 22. ''midterm exam'' | * Thus Oct 22. ''midterm exam'' | ||
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* Tues Oct 27. [[Class meeting for 10-605 Randomized|Randomized Algorithms 1]] | * Tues Oct 27. [[Class meeting for 10-605 Randomized|Randomized Algorithms 1]] | ||
* Thus Oct 29. [[Class meeting for 10-605 Randomized|Randomized Algorithms 2]] | * Thus Oct 29. [[Class meeting for 10-605 Randomized|Randomized Algorithms 2]] | ||
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* 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]] | ||
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* Thus Nov 26. ''Happy Thanksgiving!'' | * Thus Nov 26. ''Happy Thanksgiving!'' | ||
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* Tues Dec 1. [[Class meeting for 10-605 First-Order Logics|First-order logics]] | * Tues Dec 1. [[Class meeting for 10-605 First-Order Logics|First-order logics]] | ||
Revision as of 17:11, 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.
- 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
- 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
- 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!
- 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.
