In the field of neural networks, activation functions play an important role in transforming linear output into nonlinear, allowing models to learn complex patterns efficiently. Two commonly used activation functions are the Sigmoid and Softmax functions. In this article, we will be looking at the differences between these two activation functions and their respective use cases. https://www.nomidl.com/deep-learning/what-is-the-difference-between-sigmoid-and-softmax-activation-function/