Instantiation of generate-exam.md for the standard midterm. Read that file for the LaTeX conventions and workflow; use these parameters.

Parameter	Value
Exam type	midterm
Agenda	docs/agenda/<term>.md, Meetings 1–8 (through Model Training and Evaluation)
Past exams	docs/midterm/<YYYY>/ — the two or three most recent
Length	4 pages, 50 points, designed for 30–40 minutes; ends with a 3-point feedback section
Must include	one question on Assignment 1; questions on the hands-ons covered so far (packet capture, scanning, QoE, netml features, pipeline)
Instructor output	/Users/feamster/Dropbox/Tmp/exams/ml-systems/midterm/<YYYY>/ (not committed until after the exam)

Topics that recur on midterms: motivating applications (QoE, security, resource allocation); passive vs. active measurement and flow records; feature engineering and representation; data quality (missing, non-representative, irrelevant features, outliers, the TTL example); the pipeline (split, cross-validation, leakage); evaluation metrics; bias–variance; drift.