Question 1
Consider the following data point and weight vector in a simple single layer neural network. (Assume that there is no bias.) x = [1,0] w = [0,1] Once the data flows through the simple network and is passed through the activation function, the final output comes out to be 0.5. Once you have identified the activation function, enter the maximum value that the derivative of the activation function can take.