If you're interested in exploring alternative activation functions, I recommend that you try and track down a relatively obscure 1991 research paper titled, "Efficient Activation Functions for the ...

This article describes what neural network activation functions are, explains why activation functions are necessary, describes three common activation functions, gives guidance on when to use a ...

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! # ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

A neural network is a graph of nodes called neurons. ... In this case, we use the Sigmoid activation function, which compresses values into a -1 to 1 range.

A backpropagation network is a fully connected, layered, and feed-forward neural network (see Figure 4). Network activation flows in one direction only: from the input layer to the output layer ...