Activation Functions
Explore the role of activation functions in neural networks, including sigmoid, tanh, relu variants, and softmax. Understand how these non-linear functions transform neuron outputs and impact training performance. This lesson equips you to implement and optimize these functions for better model accuracy.
We'll cover the following...
We'll cover the following...
Activation functions are non-linear functions that determine the outputs of neurons. As we already discussed, each neuron accepts a set of inputs, multiplies them by the weights, sums them up, and adds a bias.
Because that will result in a linear transformation, we then pass neurons through a non-linear function ...