What are hyperparameters in neural networks?

What are hyperparameters in neural networks?

Hyperparameters are settings that you configure before training a neural network, like learning rate and batch size.

How do I choose the right hyperparameters?

Choosing hyperparameters often involves experimentation, using techniques like grid search or random search.

Can hyperparameters affect model performance?

Yes, the right hyperparameters can significantly improve model performance, while poor choices can lead to overfitting or underfitting.

What are some common hyperparameters I should know about?

Common hyperparameters include learning rate, number of layers, number of neurons per layer, and dropout rate.