Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2012

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This is the syllabus for Machine Learning with Large Datasets 10-605 in Spring 2012.

January

February

  • Thus Feb 2. More on streaming algorithms: Rocchio, and theory of on-line learning
  • Tues Feb 7. More on streaming algorithms: parallelized voted perceptron.
    • Assignment due: streaming Naive Bayes 2 (with feature counts on disk) with stream-and-sort
    • New Assignment: phrase finding with stream-and-sort
  • Thus Feb 9. Map-reduce and Hadoop 1 (Alona lecture).
  • Tues Feb 14. Map-reduce and Hadoop 2. (Alona lecture).
    • Assignment due: phrase finding with stream-and-sort
    • New Assignment: Naive Bayes with Hadoop
  • Thus Feb 16. Naive Bayes and Logistic regression.
  • Tues Feb 21. Logistic regression with stochastic gradient descent, parallel SGD
    • New Assignment: Phrase-finding with Hadoop
  • Thus Feb 23. Tentative: Guest lecture on Scaling up Machine Learning, Ron Bekkerman, LinkedIn
  • Tues Feb 28. Bloom Filters and Locality sensitive hashing 1.
    • Hadoop assignments due
    • New Assignment: memory-efficient SGD

March

  • Thus Mar 1. Bloom Filters and Locality sensitive hashing 2.
  • Tues Mar 6. Learning on graphs. PageRank, Harmonic field, RWR; tools and design patterns for graphs (Pregel, GraphLab, Schimmy, ...)
    • Assignment due: memory-efficient SGD
    • New assignment: mini-project proposals (first draft).
  • Thus Mar 8. Guest Lecture: Joey Gonzales, CMU, GraphLab and Dynamic Asynchronous Computation
  • Tues Mar 13. no class - spring break.
  • Thus Mar 15. no class - spring break.
  • Tues Mar 20. Spectral clustering and PIC.
    • Assignment due: mini-project proposals (first draft).
    • New Assignment: Subsampling and visualizing a graph.
  • Thus Mar 22. Tentative: Guest lecture by U Kang, CMU.
  • Tues Mar 27. Gibbs sampling and LDA.
    • Assignment due: Subsampling and visualizing a graph.
    • New Assignment: mini-project proposals (final version)
  • Thus Mar 29. KNN classification and inverted indices.
    • Assignment due: mini-project proposals (final version).

April

  • Tues Apr 3. Decision trees and random forests 1.
  • Thus Apr 5. Decision trees and random forests 2.
  • Tues Apr 10. Soft joins with KNN and inverted indices 1.
  • Thus Apr 12. Soft joins with KNN and inverted indices 1.
  • Tues Apr 17. Structured prediction 1.
  • Thus Apr 19. no class - Carnival
  • Tues Apr 24. Structured prediction 2.
  • Thus Apr 26. Additional topics.

May

  • Tues May 1. Project reports.
  • Thus May 3. Project reports.