Difference between revisions of "10-601 SSL"

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* How matrix factorization can be used for CF.
 
* How matrix factorization can be used for CF.
 
* How PCA, SVD, k-means, and other clustering methods relate to matrix factorization.
 
* How PCA, SVD, k-means, and other clustering methods relate to matrix factorization.
 +
* Why computer scientists tend to get Halloween and Christmas confused.

Revision as of 16:14, 30 October 2013

Slides

Readings

  • This is not covered in Mitchell.

Summary

You should know:

  • What collaborative filtering is.
  • How nearest-neighbor methods for CF work.
  • How to formulate CF as a regression or classification problem.
  • How matrix factorization can be used for CF.
  • How PCA, SVD, k-means, and other clustering methods relate to matrix factorization.
  • Why computer scientists tend to get Halloween and Christmas confused.