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