Omind Data Scientist Interview Questions and Answers

Overfitting occurs when a model learns the training data too well, leading to poor performance on new, unseen data.

• Overfitting occurs when a model is too complex and captures noise in the training data.

• It can be identified when a model performs well on training data but poorly on test data.

• Techniques to prevent overfitting include cross-validation, regularization, and early stopping.

• Example: A decision tree with too ma...read more