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...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigationJump to search

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