What is an activation function in Keras?

What is an activation function in Keras?

An activation function in Keras is a mathematical function that determines the output of a neural network node. It introduces non-linearity into the model, allowing it to learn complex patterns.

Can you give me examples of activation functions used in Keras?

Sure! Common activation functions in Keras include ReLU (Rectified Linear Unit), Sigmoid, Tanh, and Softmax.

When should I use the ReLU activation function?

ReLU is often used in hidden layers of deep learning models because it helps mitigate the vanishing gradient problem and speeds up training.

What about the Softmax function?

Softmax is typically used in the output layer of a multi-class classification model, as it converts logits into probabilities that sum to one.