Data Mining: A Statistical Learning Perspective

CS 395T/CAM 395T

CS Unique No. 55211 / CAM Unique No. 64628

Spring 2007
MW 9:30-11am
PAR 303

Instructor: Inderjit Dhillon (send email)
Office: ACES 2.332
Office Hours: M 11am-noon and by appointment

TA: Brian Kulis
Office: TAY 137
Office Hours: Tue 1-2pm and Fri 10-11am

Handouts

  • Course Information (contains grading information) to be handed out on first class day.
  • Class Survey.

    • Textbook

  • "Elements of Statistical Learning: Data Mining, Inference, and Prediction" by T. Hastie, R. Tibshirani, J. Friedman, Springer-Verlag, 2001.

    • Homeworks

  • Homework 1
  • Homework 2
  • Homework 3
  • Homework 4
  • Homework 5

    • Student Presentations
  • Suggestions for Paper Readings

    Class Projects
  • Project Suggestions

    • Syllabus

  • Overview of Supervised Learning
  • Linear Methods for Regression
  • Linear Methods for Classification
  • Kernel Methods
  • Model Assessment and Selection
  • Support Vector Machines
  • Prototype Methods and Nearest-Neighbors
  • Unsupervised Learning

    • Other References

  • "Pattern Recognition and Machine Learning" by C. Bishop, Springer, 2006.
  • "Pattern Classification" by R. Duda, P. Hart and D. Stork, John Wiley and Sons, 2000.