38. Overfitting and Underfitting in Machine Learning
Training 100% — test flop. Te overfitting. Donhi weak — underfitting. Gap bagha, simple fixes lavuya.
What you will learn in this chapter
- Define overfit vs underfit
- Spot them with train vs test scores
- Apply simple fixes
- Run a tiny depth comparison
- Practice before the end-to-end project
Fictional data
Blinkit / Amazon Now / Mauli Dairy figures in this chapter are fictional sample data for learning only. They do not show real company numbers. People names are for practice; e-mails use example.com.
Concepts in this chapter
- 38.1Too Fit vs Too Weak
- 38.2Spot It with Train vs Test Scores
- 38.3Simple Fixes
- 38.4Tiny Depth Demo
- 38.5Practice, Tip and Close
The chapter recap is at the end of the last concept page.