Statistical foundations of machine learning
Autumn 2007

Please report any dead links to me.


Soumen Chakrabarti
Teaching assistants
Rajiv Khanna , Dhaval Makawana
Time and place
As per the latest timetable, we are in slot 19, i.e., Tue 2:00--3:25 and Fri 3:30--4:55, in classroom SIC301. The first lecture will be on Fri 2007/07/27.
Visit the Moodle site for CS705 here.
Syllabus and lecture calendar
See the moodle page or the fossilized edition.
Course newsgroup
Watch cse.cs705 (internal access) on for announcements.
To be worked out in small groups of 2--3 students.


Credit students will need to write a midterm (30%) and a final (45%), and do a few assignments, typically using Scilab, WEKA, and perhaps Java (25%).

Audit students have to write only the final exam and, to pass, their score must be above the bottom 20 percent of the class in finals only.

Grades have been finalized and are kept in a password-protected area.

Midterm and final course feedback from students.


Primary books
Supplementary books
Additional reading
Software and manuals


Mtech1 and DD4s who have not yet taken CS610 are the primary targets for this course. But it is open to all PG, DD and Btech4 students of all departments subject to department/facad approval. If you are CSE Btech3, ask for my consent by email while citing your CPI and grades in Paradigms and Prob/Stat.

This course should be reasonably simple if you have a little background in vector algebra, calculus, and probability. Some basic algorithms background may also help.

CS610 in Spring 2008 will list CS705 in Autumn 2007 as a prerequisite.