32. Features and Labels in Machine Learning
32.5 Practice, Tip and Close
Why. Foundations close when you can name X, y, and one leakage risk without notes.
How.
Chapter practice
- Invent a supervised problem for Mauli Dairy (e.g. predict “will pedha tray sell out by 6 PM”).
- Write y’s exact definition.
- List 5 candidate features; mark numeric/category/text.
- Strike any leaky column and say why.
- Build a 10-row fictional pandas table and form X, y.
Practice task
In one notebook cell, assert set(X.columns).isdisjoint({y.name}) so the label never sits inside X by mistake.
Thodkyaat sangaycha tar (quick recap)
- X = features (inputs); y = label (answer)
- Numeric / category / text need different care
- Leakage = cheating with future or answer-like columns
- Build X, y explicitly in pandas before any model
Samajla ka? Foundations complete. Next: Chapter 33 — Linear Regression in Python with sklearn (first model that predicts a number).