How do I tune regularization parameters in Keras?

How do I tune regularization parameters in Keras?

Tuning regularization parameters in Keras involves adjusting values like L1, L2, or dropout rates to prevent overfitting.

What are the common regularization techniques I can use?

Common techniques include L1 regularization, L2 regularization, and dropout. Each has its own advantages.

How do I implement L2 regularization in my model?

You can implement L2 regularization by adding a kernel_regularizer parameter in your layer, like this: Dense(64, kernel_regularizer=l2(0.01)).

What should I consider when choosing the regularization strength?

Consider the complexity of your model and the amount of training data. A higher strength can help with overfitting but may underfit.