Welcome to CSI5387, Data Mining and Machine Learning: Concepts, Techniques, and Applications
Offered in the Fall 2012 semester (Sep. –
Fri 4-7PM, CBY B012
Class starts Sep. 7.
CBY building is in the southern part of the uOttawa campus.
Check the map at http://www.uottawa.ca/maps/
Instructor: Dr. Stan Matwin
This course is
changed from year to year, and the existing
slides may be modified.
If you have not taken an AI class:
I recommend you read the following chapters from "AI: the Modern Approach" by Russeell, Norvig, 3rd edition:
Assignment 1 marks are here.
Some marks are still TBD.
Here is project statement
Course marks (including project and final exam) will be here
Dec. 14,4-7PM, CBY B205
additional material for class 1 and 2 (by V. Kumar, University of Minnessota)
additional material on instability of DTs for class 3
additional slides on instability of DTs for class 3 (with thanks to Rob Holte and Ken Dwyer, U of A)
additional material on PAC for class 3
cost curves slides by Dr.C. Drummond
I do not recommend a single textbook for this class because there isn’t one that will cover all our needs. I will use material from three books:
T., “Machine Learning”. This is an excellent book, but at this
quite a bit outdated. Tom promises to finish a new edition, and
Hastie, T. Tibshirani, R. Friedman, J., "The Elements of Statistical Learning", an excellent textbook for part of the material, with a highly mathematical slant
Cornuéjols, A., Miclet, L.
artificiel: consepts et algorithmes" (don’t worry, you can make
this class without knowing French)
Han, J., Kamber, M. "Data Mining. Concepts and techniques"
And no panic, you do NOT need to buy five or six books. I am working to have all of them on reserve in the uOttawa library. Some of these books are available s e-books, and only chapters will be recommended as additional reading The main material for the course will be my .ppt slides and the papers listed below.