Project and Review#
Final project — Sessions 27–28
Project shape#
Data preparation and problem framing
Select and implement several models (e.g. local, linear, kernel, probabilistic)
Evaluate with standard metrics and compare
Write a short scientific report
Review#
Course recap, connections between topics, and preparation for exams.