Assignments
Assignment Structure
Each homework will comprise of an approximate mix of 50% written questions and 50% coding questions. The written portion of the assignment will be submitted in a Google Form (resubmittable till the due date of the respective assignments). The coding portion will have to be completed in the iPython notebook provided.
Assignments
The assignments will be released on Campuswire.
| Assignment | Release Date | Due Date |
|---|---|---|
| HW 1: Math Foundations for ML | September 6 | September 20 |
| HW 2: Linear Regularization | September 20 | October 4 |
| HW 3: Support Vector Machines | October 4 | October 18 |
| HW 4: Random Forests | October 18 | November 3 |
| HW 5: Convolutional Neural Networks | November 3 | November 17 |
| HW 6: Dimensionality Reduction | November 17 | December 1 |
Collaboration Policy
The work you submit for assignments is expected to be entirely your own without collaboration. For the assignments, we will use a “mission command” approach. This means that we will tell you what we want you to do, not how. It is known to foster creative problem solving skills. In practice, this means that you can solve the problems using any means at your disposal (if you are comfortable with them) in addition to those taught in this class.