There will be three assignments throughout the semester, focusing on theoretical and practical issues related to deep learning. The assignments are due just before midnight, at 11:55 pm, unless otherwise specified. The tentative due dates are listed below.
You will submit the assignments electronically through Gradescope (do not email your assignments). You will be automatically enrolled in Gradescope at the start of the semester.
More details on the submission process will be provided with each homework.
Late day policy:
Re-grading policy: Errors in grading of assignments and exams can occur despite the best efforts of the course staff. If you believe you’ve found a grading error, submit a re-grade request on gradescope. Re-grade requests must be submitted no later than one week after the assignment is returned. Note that re-grading may result in your original grade increasing or decreasing as appropriate.
Assignment | Due Date | Description |
---|---|---|
Assignment #1 | Thursday, Sept 26, 11:55pm | Image Classification, kNN, SVM, Softmax, Neural Network |
Assignment #2 | Thursday, Oct 24, 11:55pm | Fully-Connected Nets, Batch Normalization, Dropout, Convolutional Nets |
Assignment #3 | Tuesday, Nov 26, 11:55pm | Image Captioning, Self-Supervised Learning, Style Transfer |