Data Mining and Machine Learning

• Final score
• Instructor: Chih-Jen Lin, Room 413, CSIE building.
• TA:
• BBS:
• Time: Monday 9:10am-12pm, Room 105, CSIE building.

  No course at November 18 (attend a conference in Singapore)
  We will have courses from 9-12:30 in several weeks.

• Textbook: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations by Ian H. Witten and Eibe Frank.
  
• Lecture slides: downloadable from the Morgan Kaufmann web site
  See the item "PDF slides" of the teaching material

  SVM slides used can be downloaded here

• Reference:
  • Machine Learning, Tom Mitchell, McGraw Hill, 1997.

Course Outline (tentative)

• Input: Concepts, Instances, Attributes
• Output: Knowledge Representation
• Algorithms: The Basic Methods
• Credibility: Evaluating What's Been Learned
• Implementations: Real Machine Learning Schemes
• Engineering the Input and Output
• Machine Learning Algorithms In Java

Homework

• hw1, due October 7, 2002.
• hw2, due October 28, 2002.
• hw3, due November 11, 2002.
• hw4, due December 9, 2002.
• hw5, due December 23, 2002.
• hw6, due January 6, 2003.

Exams

• Midterm: November 4, 2002
• Final: January 6, 2003

  We will discuss the final exam at January 9, 1-2pm. (in room 105)

Final Projects

Grading

Related Information

• Kdnuggets: a useful collection of data mining related software, book, and many other stuff.