juniorNeural Networks
What is overfitting?
Updated May 17, 2026
Short answer
Overfitting occurs when a model learns training data too well, including noise.
Deep explanation
It results in high training accuracy but poor generalization on unseen data. Techniques like dropout and regularization help reduce it.
Real-world example
A model memorizing training images instead of learning patterns.
Common mistakes
- Using overly complex models without regularization.
Follow-up questions
- What is dropout?
- How to detect overfitting?