Difference between revisions of "10-601 SSL"
From Cohen Courses
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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 15:14, 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.
