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Carnegie Mellon University
95-828 Machine Learning for Problem Solving
Spring 2026

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Coursework

Coursework consist of (grading in parentheses):

  • 5 Homework (10% each)
  • 1 Midterm exam (15%)
  • 1 Final exam (25%)
  • Participation via (Canvas) Quizzes (10%)

HOMEWORK:

Homework will be posted on Canvas. Each homework will consist of two parts: (1) a set of conceptual questions, and (2) programming. For the programming part, we will provide a code template (and sometimes partial code as well) in a Jupyter notebook. You will have two weeks to complete each homework assignment.

Getting help: You can visit the instructor and the TAs during office hours as well as post questions on Piazza to get help on the assignments. Regarding help from fellow students, see the note on collaboration below.

Collaboration: All assignments are to be written individually. Collaboration and study groups are allowed and encouraged. However, each student should submit their own write-up. Please see the collaboration policy for details.

Submitting: We ask that you submit two files per homework: (1) a pdf file with your answers to the conceptual questions, and (2) the Jupyter notebook we provide as a template with all your code that you filled in. Both files (.pdf and .ipynb) are to be uploaded electronically only on Gradescope (no hard-copy print-outs).

Homework assignments are due at the beginning of the class on the day it is due. You can upload your files multiple times, but note that we will use the latest upload date as the submission date, which may factor into your slip days accordingly. Please see the late submission policy for details.

IMPORTANT DATES:

Assignment Note Out Due Weight
Homework 0
Setting up Python/PyTorch, PSC, and Jupyter
Jan 16
n/a
0%
Homework 1
EDA, LR, LogR, Model selection
Jan 26
Feb 6
10%
Homework 2
HPO, Non-parametric, DT
Feb 6
Feb 20
10%
Midterm Exam
(in class)
Feb 27
--
15%
Homework 3
Ensembles, Neural Nets and Transformer
Mar 11
Mar 25
10%
Homework 4
Important concepts, Learning paradigms, Unsupervised ML
Mar 25
Apr 8
10%
Homework 5
ML for text / time series / tabular data / graphs
Apr 8
Apr 24
10%
Final Exam

Check out
univ. calendar
--
25%

EXAMS:

There will be a midterm exam (in class) and a final exam (to be scheduled by the University).

Note: For the midterm, you are allowed to bring with you 2 A4-size sheets, containing your own notes (hand-written or typed). You can use both sides of each sheet. For the final, you are allowed to bring up to 5 A4-size sheets (double sided), again containing your own notes.

Use of any computers or other electronic devices during the exams is not allowed. The tentative dates are posted above, the finalized dates will be announced during the semester.