CIS 4930.007/6930.002: Data Mining in Bioinformatics

Spring 2011

 


Instructor: Xiaoning Qian [Office: ENB 317; Phone: 813-974-9653; Office Hours: T/TR 10:00–12:00 or by email appointment]

Time & location (tentative): Tue/Thu 15:30-16:45 @ NES 103

Grading: Homework assignments (60%) + Final project (20%) + Final exam (20%)


 

Objectives: This course will introduce basic machine learning and data mining techniques and their applications in many fields, including signal processing, computer vision, and especially in bioinformatics. The major topics include linear and non-linear models in supervised learning, unsupervised learning, structured learning, ensemble learning, and feature selection.

Main textbook: Chris Bishop, Pattern Recognition and Machine Learning (ISBN 0387310738)

Recommended readings:  Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani and Jerome Friedman (ISBN 0387952845)

   Data Mining (Second Edition) by Ian Witten and Eibe Frank (ISBN 0120884070)

   Check Blackboard for updates!!


 

Announcements:

 

·  Course flyer [flyer] is posted on Oct. 22nd, 2010.

·  Course syllabus [syllabus] is posted on Oct. 28th, 2010.

·  First week classes (01/03/2011): I have posted an announcement on Blackboard about the classes for the first week. I am sorry that I have to be out of town for a conference for the first week. Prof. Yu Sun has kindly offered to cover the first class on 01/11. The class on 01/13 will be cancelled. Please send your emails to either me or Meng Lu if you have any questions.

 

 

Handouts:

 

·  Handout #1 –[Review of linear Algebra] from Dr. Andrew Ng's Machine Learning course was posted on Dec. 16th, 2010.

·  Handout #2 –[Review of Probability Theory] from Dr. Andrew Ng's Machine Learning course was posted on Dec. 16th, 2010.

·  Handout #3 –[Slides from Lecture 1] has been posted as well as on Blackboard on Jan. 19th, 2011.

 

Check Blackboard for updates

 

 

 

Homework assignments:

 

·  Homework #1, Check Blackboard for updates

 

 

Final projects:

 

·  Project proposals

 

 


 

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