There are 10 written assignments in total. All assignments are due at noon Central Time (not midnight). See syllabus for more detailed schedule regarding due dates.
Assignment 1: Linear Regression
[pdf] [A1_LinearRegression.py] [A1_LinearRegression2.py] [Solution] [Programming Solution]
Assignment 2: Logistic Regression
[pdf] [A2_LogisticRegression.py] [A2_LogisticRegression2.py] [A2_LogisticRegression3.py] [Solution] [Programming Solution]
Assignment 3: Support Vector Machine
Assignment 4: Multiclass Classification
Assignment 5: Deep Nets
Assignment 6: Structured Prediction
Assignment 7: k-Means
Assignment 8: VAEs
Assignment 9: GANs
Assignment 10: Reinforce
MNIST download: [Zipped Files] [train-labels-idx1-ubyte] [t10k-images-idx3-ubyte] [t10k-labels-idx1-ubyte]
Written assignments are submitted through GradeScope (self-enrollment code 9ZG73B; please use your Illinois email when registering on GradeScope).
Download the assignment,
Print the assignment,
Complete the answers (make sure your handwriting is readable),
Add your name on every page,
Scan the printed document containing your answers (make sure it’s a pdf), and
Upload on gradescope.
Some questions are related to the coding assignment. Note that you don’t upload your python code (we don’t need it).
Feel free to discuss the assignments at the concept-level with other students, no specifics.
All solutions should be written individually.
Do not show other students your homework. (This includes Piazza. Do not post partial code or solutions.)
Be sure to acknowledge references you used.
Copying from other students / online sources or letting other students copy your work will result in a 0 for the assignment. A second attempt of cheating will result in grade F for the entire course.
Check the Student Code on academic integrity here.
Late submission will not be accepted after the due date. The lowest scoring homework will be dropped.