What is overfitting and how does the learning rate affect it?

What is overfitting in machine learning?

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

How does the learning rate influence overfitting?

A high learning rate can cause the model to converge too quickly, potentially leading to overfitting, while a low rate may help generalize better.

Can you give me an example of overfitting?

Sure! Imagine a model trained on a small dataset of images that memorizes every detail instead of learning to recognize general features.

What techniques can I use to prevent overfitting?

You can use techniques like cross-validation, regularization, and dropout to help prevent overfitting in your models.