General Info
Assessment
Materials
  Sources on the Internet
  Files
Assignments
Timetable
      

CPSC 599.44: Machine Learning - Materials


Textbooks

The following is a collection of text books on Machine Learning including links to electronic versions of them (resp. the publishers' pages pointing to them; note that our library has agreements with many publishers that allow you to access these electronic versions) if they are available. None of them covers all of the course, but most of the topics of the course are at least covered by one of the books.


Other Sources on the Internet

There are several sites collecting links about machine learning:


Files to the course

The slides containing the general information on a particular topic that I use in the lectures will be available before the respective lectures here as Acrobat pdf-files (in two formats: one slide per page and the 6 slides per page handout).

Date handout format one slide per page
Jan. 9 Introduction Introduction
Jan. 18 Learning Rules Learning Rules
Jan. 26 Learning Parameters: Linear Regression Learning Parameters: Linear Regression
Feb. 2 Learning Parameters: Support vector machines Learning Parameters: Support vector machines
Feb. 8 Learning Trees and Graphs: ID3 Learning Trees and Graphs: ID3
Feb. 11 Learning Trees and Graphs: Bayesian networks Learning Trees and Graphs: Bayesian networks
Feb. 22 Learning Partitions of a set Learning Partitions of a set
Mar. 7 Learning Sequences and Behaviors Learning Sequences and Behaviors
Mar. 15 Case-based/Analogical Reasoning Case-based/Analogical Reasoning
Mar. 29 General improvement techniques General improvement techniques
Apr. 7 General improvement techniques General improvement techniques

to the assignments of the course.

Last Change: 7/4/2016