46. Deep Learning vs Classical ML: When to Use Which
46.1 When Classical ML Is Enough
Why. Deep learning is not a default for every Excel-sized problem. Classical sklearn often wins on small clean tables.
What. Prefer logistic / trees / forests when you have hundreds–thousands of structured rows, strong tabular features, and need fast training on a laptop.
How.
Classical-first checklist
- Is the data a table (not raw images/audio)?
- Can a human name the useful columns?
- Is the dataset modest?
- If yes → start with Chapters 33–39 tools.
print("Small shop reorder table -> LogisticRegression / RandomForest first")