What is overfitting in machine learning, and how can it be prevented?

Overfitting occurs when a model learns not only the underlying pattern in the training data but also the noise. This leads to poor generalization to unseen data. To prevent overfitting:

* Use techniques like cross-validation to assess the model’s performance.
* Regularize the model (L2/L1 regularization).
* Use simpler models or reduce the number of features.
* Use more data to train the model.