Activation Functions in Neural Networks Explained Simply With Types & Examples

AI • Machine Learning • Tech on Instagram: "A feed-forward neural network processes inputs through sequential layers (input → hidden → output). Each neuron computes a weighted sum of its inputs, adds a bias, then applies an activation function (ReLU, sigmoid, etc.) to introduce non-linearity. These transformed values are passed forward, layer by layer, with outputs from one layer becoming inputs for the next, producing predictions through mathematical transformations. C: emergent garden Join our