Difference between revisions of "Class meeting for 10-605 2013 02 13"
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* Map-reduce-like frameworks and wrappers | * Map-reduce-like frameworks and wrappers | ||
− | ** [http://www.cs.cmu.edu/~wcohen/10-605/2013-02-13-hadoop+.pptx Slides in Powerpoint] | + | ** [http://www.cs.cmu.edu/~wcohen/10-605/2013/2013-02-13-hadoop+.pptx Slides in Powerpoint] |
* Stochastic gradient descent for logistic regression | * Stochastic gradient descent for logistic regression | ||
− | ** [http://www.cs.cmu.edu/~wcohen/10-605/2013-02-13-sgd.pptx Slides in Powerpoint] | + | ** [http://www.cs.cmu.edu/~wcohen/10-605/2013/2013-02-13-sgd.pptx Slides in Powerpoint] |
=== Readings for the Class === | === Readings for the Class === | ||
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=== Optional readings === | === Optional readings === | ||
− | * I also recommend [http://www.cs.cmu.edu/~wcohen/10-605/notes/elkan-logreg.pdf Charles Elkan's notes on logistic regression] | + | * I also recommend [http://www.cs.cmu.edu/~wcohen/10-605/notes/elkan-logreg.pdf Charles Elkan's notes on logistic regression] (local saved copy). |
Latest revision as of 17:13, 8 January 2014
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Spring_2013.
Slides
- Map-reduce-like frameworks and wrappers
- Stochastic gradient descent for logistic regression
Readings for the Class
- Pigs Bees and Elephants (web page)
- William's notes on SGD
- Lazy Sparse Stochastic Gradient Descent for Regularized Multinomial Logistic Regression, Carpenter, Bob. 2008. See also his blog post on logistic regression.
Optional readings
- I also recommend Charles Elkan's notes on logistic regression (local saved copy).