10-601 Course Overview
From Cohen Courses
Revision as of 09:59, 14 January 2016 by Tdick (talk | contribs) (Created page with "This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016 === Slides === * [http://www.cs.cmu.edu/~wcohen/10-601/prob-tour+bayes.pptx Slides in Pow...")
This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016
Slides
Readings
- Mitchell Chap 1,2; 6.1-6.3.
What You Should Know Afterward
You should know the definitions of the following, and be able to use them to solve problems:
- Machine learning examples
- Well defined machine learning problem
- Decision tree learning