CMU 10-301 HW1: Find ML Foundation Gaps with Mathematics and Python

🌏 中文版

The official handout inside the ZIP is titled Homework 1: Background and contains written plus programming work. Written sections cover course policies, probability and statistics, linear algebra, calculus, geometry, and CS foundations. The programming component is a majority-vote classifier that reads TSV files and writes train/test labels and error metrics. The ZIP supplies heart and education splits, a LaTeX template, and reference outputs, but no majority_vote.py starter; hidden grading remains on Gradescope.

The capability being tested

Translate notation into array shapes, loops, and exact command-line output. Record inputs, outputs, and dimensions after each derivation. For code, hand-compute a tiny case before comparing with the supplied example output. Classify disagreements as mathematical, indexing, or formatting failures.

First executable action

After extracting the ZIP and creating majority_vote.py, run the handout's interface:

python majority_vote.py heart_train.tsv heart_test.tsv heart_train_labels.txt heart_test_labels.txt heart_metrics.txt

Then add tiny cases for reordered columns and constant labels. Completion means explaining the shapes in the main mathematics sections and matching both heart and education reference label/metric files line by line. It does not establish success on private tests.

References

• Spring 2026 coursework
• HW1 public bundle