Difference between revisions of "Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2013"

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* Wed Feb 13. [[Class meeting for 10-605 2013 02 13|Hadoop helpers and Scalable SGD]]
 
* Wed Feb 13. [[Class meeting for 10-605 2013 02 13|Hadoop helpers and Scalable SGD]]
 
* Mon Feb 18. [[Class meeting for 10-605 2013 02 18|Scalable SGD and Hash Kernels]]
 
* Mon Feb 18. [[Class meeting for 10-605 2013 02 18|Scalable SGD and Hash Kernels]]
** '''Streaming run on Hadoop of Naive Bayes due'''
+
** '''Streaming run on Hadoop of Naive Bayes due''' - checkpoint
 
* Wed Feb 20. '' Guest lecture: Chris Dyer.  Scalable feature selection with Map-Reduce.''
 
* Wed Feb 20. '' Guest lecture: Chris Dyer.  Scalable feature selection with Map-Reduce.''
 
* Mon Feb 25. [[Class meeting for 10-605 2013 02 25|Background on randomized algorithms; Graph computations 1.]]
 
* Mon Feb 25. [[Class meeting for 10-605 2013 02 25|Background on randomized algorithms; Graph computations 1.]]

Revision as of 12:26, 4 February 2013

This is the syllabus for Machine Learning with Large Datasets 10-605 in Spring 2013.

January

February

March

April and May

May

  • Fri May 3.
    • Project writeups due at 5:00pm. Submit a paper to Blackbook in PDF in the ICML 2013 format (up to 8pp double column), except, of course, do not submit it anonymously.