SUBHANKAR MISHRA

ଶୁଭଙ୍କର ମିଶ୍ର

Faculty member, School of Computer Sciences, NISER
ଅଧ୍ୟାପକ, ସଂଗଣକ ବିଜ୍ଞାନ ବିଦ୍ୟାଳୟ, ନାଇଜର



CS460/660 - Machine Learning 2026 (Odd Semester)

Syllabus

Expected skills (no mandatory prerequisite)

Grading scheme

Absolute grading.
Component Marks
Midterm [10]
Endterm [40]
Project Distribution (Proposal 05, Midway1 10, Midway2 10, Final 25) [50]
Extra Credit Paper Submission (deadline: December 12) [10]
Total [100]

Lectures

Lecture schedule will be announced in class and updated here as the course progresses.


Project

Individual project; develop something new this semester using a dataset, implementation, or analysis.

Report template: LaTeX source | PDF sample

Project timeline

# Date Focus / limit Report PDF LaTeX source
1 27 August 2026 Base paper, problem, data, and tentative deliverables; 2 slides Proposal: none PDF TeX
2 14-15 September 2026 Maximum 5 slides Midway1: 1 page PDF TeX
3 26-27 October 2026 Maximum 6 slides Midway2: 1 page PDF TeX
4 16-17 November 2026 Maximum 10 slides Final: 2 pages PDF TeX

Slide structure

Project entries

# Student Title Proposal Midway1 Midway2 Final
1 Student Name Title P1 P2 P3 P4
None Midway1 Midway2 Final

Books

Recommended: The Elements of Statistical Learning | Mathematics for Machine Learning | Introduction to Machine Learning with Python | A Course in Machine Learning


AI policy

Students are free to use AI tools for assistance. However, the content presented remains the student's own work. Slides and reports must be prepared manually by the student. If a student cannot answer the details presented by AI or cannot explain the work in the viva, the submission may receive zero.


Academic Integrity

Any plagiarism, copying, allowing copying, unpermitted aid will lead to 'zero' in the assignment/exam/project.

Past Courses