33. Linear Regression in Python with sklearn
33.6 Practice, Tip and Close
Why. Close the chapter when you can fit LinearRegression, read coef_, and avoid one classic mistake without notes.
How.
Chapter practice
- Build a 12-row fictional table: daily_pedha_sales vs temperature_c for Mauli Dairy Nashik.
- Split, fit LinearRegression, print intercept_ and coef_.
- Predict sales for a new day at 36°C.
- Write one sentence: “Each extra °C changes predicted sales by about ___ trays.”
- List two mistakes you will refuse in a real notebook.
Practice task
Add a second feature is_weekend (0/1). Refit. Explain both coefficients in Marathi or English in one line each.
Thodkyaat sangaycha tar (quick recap)
- Regression predicts a number (₹, kg, minutes)
- LinearRegression learns intercept_ + coef_
- Always split; never put y inside X
- Read coef_ in business units, carefully
Samajla ka? Next: Chapter 34 — Classification with Logistic Regression (yes/no answers).