CS 403 Foundations of Machine Learning (Autumn 2017-18)

Instructor Name: Ganesh Ramakrishnan

Course Type: Theory

Pre-requisites:Formal : N/A ; Informal : Any rigorous statistics course

Course Content: Regression, Neural Networks, Optimization techniques

Other topics covered: The end of the course contains topics as per time available and student requests

Books: Pattern Recognition and Machine Learning - Christopher M Bishop

Lectures: No attendance policy, however it's better to go to class, because he does cover extra stuff

Assignments:Around 2 coding assignments, Moodle quizzes

Exams and Grading: 2 quizzes (~ 7.5% each), 1 midsem (~15%), 1 endsem (~25%), Project (~20%), Assignments (~20%), Moodle quizzes (~5%)

Online material: A few of the instructor's recorded lecture videos

Follow-up Courses:Advanced Machine learning, Intelligent learning agents

Pro-tips:

Personal Comments:

Respondent: Mandar Sohoni