What is overfitting in machine learning?

Can you explain what overfitting means in machine learning?

Sure! Overfitting occurs when a model learns the training data too well, capturing noise instead of the underlying pattern.

How can I tell if my model is overfitting?

You can check the performance on a validation set. If the model performs well on training data but poorly on validation data, it's likely overfitting.

What are some ways to prevent overfitting?

Common techniques include using more training data, simplifying the model, and applying regularization methods.

Can you give an example of overfitting?

Certainly! Imagine a model that perfectly predicts the training data points but fails to generalize to new, unseen data.