What are epochs and batch size in Keras?

Can you explain what epochs and batch size mean in Keras?

Sure! In Keras, an epoch is one complete pass through the entire training dataset, while batch size refers to the number of samples processed before the model's internal parameters are updated.

Why is it important to choose the right batch size?

Choosing the right batch size can affect the training speed and the model's performance. A smaller batch size can lead to better generalization, while a larger batch size can speed up training.

How do I determine the best epoch and batch size for my model?

You can experiment with different values using techniques like cross-validation. Monitoring the model's performance on a validation set can also help you find the optimal settings.

Are there any default values I should start with?

A common starting point is to use a batch size of 32 and train for 10-50 epochs, but this can vary based on your specific dataset and model.