Comparison of Activation Functions for Deep Neural Networks

Activation functions play a key role in neural networks, so it is essential to understand the advantages and disadvantages to achieve better performance. It is necessary to start by introducing the non-linear activation functions, which is an alternative to the best known sigmoid function. It is important to remember that many different conditions are important when evaluating the final performance of activation functions. It is necessary to draw attention to the importance of mathematics and the derivative process at this point. So, if you're ready, let's roll up the sleeves and get our hands dirty!