What are the best practices for tuning deep learning models?

What are the best practices for tuning deep learning models?

Some best practices include using a validation set, adjusting learning rates, and employing regularization techniques.

How do I choose the right learning rate?

You can start with a small learning rate and use techniques like learning rate schedules or adaptive learning rates.

What is the role of batch size in training?

Batch size affects the stability of the training process and the convergence speed. Smaller batches can lead to more noise.

Can you explain overfitting and how to prevent it?

Overfitting occurs when a model learns noise in the training data. You can prevent it using techniques like dropout and early stopping.