Your course assignments (deadlines in the Schedule tab) are individual assignments and are due by 11:59 pm on the date listed. You have six (6) late days you can use during this course, and up to two (2) can be used on each assignment. These assignments are worth 80% of your course grade (20% each), and each will consist of some amount of coding and written work. The distribution of coding and written work may vary between assignments.
There will be five (5) assignments throughout the course; the first of these is optional and ungraded and will step through Python and Numpy skills; you are highly encouraged to work through this assignment. Assignments 1-4 (planned to cover regression, classification, clustering, and reinforcement learning) will be graded.
When submitting written homework, make sure your answers are selected and visible when you submit them.
You can handwrite and scan the written parts of the assignments, but the answers must be clearly visible (i.e., pencil may not work)
Please make sure to add the corresponding question tag to your solution to make grading easier.
If you feel we have made an error in grading your assignment, you can submit a regrade request on Gradescope; we will generally keep regrade requests open for 2 business days after grades are returned.
Assignment 0 is an ungraded set of Python and Numpy practice coding problems. We suggest going through these problems to practice using Python (if needed), NumPy, and Google Colab. We will provide solutions to these coding problems after the "due date", but you can still practice submitting up to a week after this assignment is due.
You can find Assignment 0 on Canvas, with more instructions (released 5pm 9/24)
Due: 9/24 (can turn in up to a week late without using late days)
Assignment 1 consists of two parts: a coding assignment and a written assignment. This homework focuses on Regression and measuring ML performance. You can find Assignment 1 on Canvas (released 10/2 5pm), with more instructions.
Due: 10/14, 11:59pm
Assignment 2 consists of two parts: a coding assignment and a written assignment. This homework focuses on Classification techniques. You can find Assignment 2 on Canvas (released 10/16 5pm), with more instructions.
Due: 10/28, 11:59pm
Assignment 3 consists of two parts: a coding assignment and a written assignment. This homework focuses on Clustering techniques. You can find Assignment 3 on Canvas (released 10/30 5pm), with more instructions.
Due: 11/18, 11:59pm
Assignment 4 consists of two parts: a coding assignment and a written assignment. This homework focuses on RL and Neural Network techniques. You can find Assignment 4 on Canvas (released 11/20 5pm), with more instructions.
Due: 12/2 12/5, 11:59pm