CS6140/4420 Supervised Machine Learning Sec 1, FALL 2023
- A friendly advanced warning on particularly time
consuming exercises: you might want to start these as
early as possible, and make sure to first read all the
discussion/posts.
- HW2 Neural Network (the autoencoder problem)
- HW4 The ECOC implementation
- HW6 The SMO solver implementation for SVM
- Discussion forum : https://piazza.com/northeastern/spring2023/ds442039372202330
Please use the piazza
discussion forum for all questions regarding material,
assignments, due dates, data issues, programming issues, etc.
That is, do not use the direct email to TAs or Instructors for
these questions.
Personal/private matters, such as availability, delays,
grades, term projects or other advanced material, etc, should be
discussed by email.
- Welcome to CS 6140- Machine
Learning. Bookmark this page! General structure of the
course:
- Seven modules (2 weeks each) with readings, lecture notes,
slides, explanations (video), recorded lectures, and of course
a homework.
- Assignments (homeworks) are focused on programing ML
techniques, training on data, test/evaluate, and
coding/engineering aspects.
- Mandatory: You are expected to participate at office hours;
either to discuss your difficulty with the assignment, or to
demo the code and results for grading.
- Each assignment is graded on the spot by a TA when you have
it working. We wont be picky with the grading, but some
assignments can be quite challenging. Often the TA will point
to something that needs more work before you can get full
credit.