39. End-to-End Machine Learning Project (India Dataset)
39.1 Project Goal (India Fictional)
Why. Separate chapters stick better when you run one thin project that ties them: features, split, model, metrics, overfit check.
What. Project goal (fictional): Mauli Dairy Nashik wants to predict whether a retail shop will place a reorder this week (1/0) from last week’s litres, SKU count, and distance_km from the plant.
How.
Write the one-pager
- Business question in one sentence.
- y definition (reorder_this_week).
- Allowed features (no leakage from “future invoice id”).
- Success view: precision/recall on a holdout week-style split (here: random split for the toy).
print("Project: classify reorder_this_week for Mauli Dairy shops (fictional).")
print("Models to try: LogisticRegression + RandomForestClassifier")
print("Score with precision, recall, confusion_matrix on test set")
Fictional data
Shop names and litres are invented for this chapter. Not Mauli’s real books.
Ravindra Bagale's Tip
Project pehle question crystal clear — code nantar.