CS 4033/5033 Machine Learning
- Required Books
- Elements of Statistical Learning by Hastie, Tibshirani, and Friedman. Note that this book is available online for free (download the latest copy, currently the 12th printing) or you can order a printed copy via Amazon or Springer.
- Reinforcement Learning: An Introduction by Sutton & Barto (available online for free)
- Note we will be using a draft copy of the 2nd edition, which is available at the above link.
- We will also make use of additional online books, papers, and other resources.
- Optional but potentially useful books:
- The course syllabus is here.
- Additional information, discussion boards, and announcements will
be available on Canvas.
- Class schedule
(updated as the semester progresses)
- Coming up with a project (note that the suggested ideas change each year and previous ideas can be useful as well! Plus you are free to come up with your own!):
- Finding related research:
- Journal of Machine Learning Research (papers available for free)
- Machine Learning Journal (expensive but some articles available for free)
- International Conference on Machine learning (2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, ... google for other years, papers are generally available for free, try citeseer or google scholar searches to find them)
- Association for the Advancement of Artificial Intelligence holds an annual conference and the past list can be found here
- Journal of Artificial Intelligence Research (papers available for free)
- Citeseer (online paper search engine) and Google Scholar (ditto)
- Acquiring data (if the source is not already specified from your project):
- Designing your experiments:
- Writing it up:
This page written by amcgovern [at] ou.edu.
August 15, 2018 1:08 PM