for linear regression type of problem, you can simply create the Output layer without any activation function as we are interested in numerical values without any transformation. more info : https://machinelearningmastery.com/regression-tutorial-keras-deep-learning-library-python/ for classification : You can use sigmoid, tanh, Softmax etc.
Yes There is! Credit: It was hard to find the information and get it working but here is an example copying from the principles and code found here and here. Requirements: Before we start, there are two requirement for this to be able to succeed. First you need to be able to write your activation … Read more
Sigmoid specifically, is used as the gating function for the three gates (in, out, and forget) in LSTM, since it outputs a value between 0 and 1, and it can either let no flow or complete flow of information throughout the gates. On the other hand, to overcome the vanishing gradient problem, we need a … Read more