Plot the histogram of activation functions for each layer in network 1 after the training is done.A3)

Responsive Centered Red Button

Need Help with this Question or something similar to this? We got you! Just fill out the order form (follow the link below), and your paper will be assigned to an expert to help you ASAP.

Learning Goal: I’m working on a python discussion question and need an explanation and answer to help me learn.A1 ) Add mini-batch stochastic gradient decent for both networks, add a function to calculate prediction accuracy for both networks.¶A2) Plot the histogram of activation functions for each layer in network 1 after the training is done.A3) Add two more hidden layers to the first network and define backpropegation accordinglyA4) add 1-2-3 more hidden layers to the network 2 and plot cost for each epoch as a line in the line plot. The color for each line should be unique based on the number of hidden layers.Your line plot should have 4 lines, Original (2 layers), 3 layers, 4 layers and 5 layers networks. Please see the code in the attached document and modify it according to the above mentioned questions. Please do in a ipynb file (jupyter).
Requirements: just need in a ipynb file and mention the question and answer number in the code

How to create Testimonial Carousel using Bootstrap5

Clients' Reviews about Our Services