Course Description

Welcome to "Foundations of Machine Learning CS 725".
In this graduate-level course, you will be introduced to the theoretical foundations of machine learning along with a slew of popular machine learning techniques.

Course Info

Time: Monday (10:35 am to 11:30 am), Tuesday (11:35 am to 12:30 pm), Thursday (8:30 am to 9:25 am)
Venue: F.C.Kohli Auditorium, KReSIT Building
Instructors: Preethi Jyothi and Ganesh Ramakrishnan. You can email us at pjyothi [at] cse [dot] iitb [dot] ac [dot] in or ganesh [at] cse [dot] iitb [dot] ac [dot] in

Instructor office hours: TBA
TA office hours: TBA

Course grading

All assignments should be completed individually. No form of collaboration is allowed unless explicitly permitted by the instructor. Anyone deviating from these standards of academic integrity will be reported to the department's disciplinary committee.

  1. Two assignment sets (20%)
  2. Two quizzes (20%)
  3. Midsem exam (15%)
  4. Project (15%)
  5. Final exam (25%)
  6. Participation (5%)


All the slides and course material, along with the class schedule, will be available on Moodle.


Most of the suggested readings will be freely available online. Here are some textbooks to refer to:

  1. Understanding Machine Learning. Shai Shalev-Shwartz and Shai Ben-David. Cambridge University Press. 2017.
  2. The Elements of Statistical Learning. Trevor Hastie, Robert Tibshirani and Jerome Friedman. Second Edition. 2009.
  3. Pattern Recognition and Machine Learning. Christopher Bishop. Springer. 2006.
  4. Foundations of Data Science. Avrim Blum, John Hopcroft and Ravindran Kannan. January 2017.

Website credit: This is based on a Jekyll template.