Neural Networks Weight matrices explained
By your description I suppose that you have two layers, where the first layer outpits a tensor of batch x 40 and the second layer a batch x 1 tensor, meanwhile the input is a tensor of batch x 80.
Then the weights dimentions are:
W1: 80x40 -> first layer
W2: 40x1-> out layer
Hi guys was wondering if anyone could help me with what I would actually answer for this question on a upcoming exam I have on AI in Python. The question confuses me as I thought I would usually need more info to answer but it is not provided. the question asked is

A Python class is used to represent a neural network and the feed forward operation is called as indicated below:
' y_hat = NN.forward(X) '
where y_hat is the output and X is the input matrix.
The neural network has an input size of 80, one hidden layer of size 40 and an output layer of size 1.
What size will be the W1 and W2 matrices?

If anyone could help me with this as my lecturer is not replying to the classes emails.
Many Thanks!