Yes

Yes.

I have an assignment but I can't do it from scratch I tried but couldn't so you know how to do it or anything? Or pass anything that I can take the code from it?

How?

You have an assignment to make one but you haven't been taught how?

Yeah. The way to do it is you need to use math

Yes, it's not only me that have problems, I asked in department's group to seek any help but no one knows anything It's something so dump tbh

Okay But how to code the neural itself Like inputs , hidden , outputs

That information has unfortunately been lost in time.

Put your exact question into google. The first... 50 links explain how to do it.

I'm sorry, but with or without an answer will just leave you in the same place.

I really did , I spent like a week on it but I still didn't know how to code the neural without sklearn or any libraries I posted cuz I lost hope that's all

I don’t think anyone really wants to do your homework for you. Because is seems unlikely you weren’t told how to do this is some form

What’s your starting point here? Are you using python? Do you get numpy?

The maths you want is something like:

acts = act(in X w1)

To get hidden activation where act is your activation function, X is a matrix multiply and w1 has dims of len(in) by hidden size.

Then you do:

out = act(acts X w2)

Where w2 has dims len(acts) by output dims

Yeah I got those I know all the basic I did all the process on the data I just can't start building the neural

The only method I know is matrix multiplication but that was just the forward part. The backward part need an understanding of partial derivation. The code will adapt according to the language...

I don't believe you spent more than 15 minutes searching for an answer, but here you go: https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6

So you will need to implement that maths in your chosen language (easiest would be python and numpy as the syntax is almost the same as I shared). That’s the forward pass from inputs to outputs. You will also need to initialise the weight matrices w1 and w2 to something. Do you have any pretrained weights you can test it with? You may also need to add biases after the matmuls depending on the brief. Usually the case but not necessarily essential to make it train.

Presumably you will also need to then train your network so it’ll get a bit more tricky. You’ll need to implement a loss function based on error between the outputs and some target variable. Once you have the loss you can then use chain rule back through the network to get the delta w (weight gradients) for each weight (w1 and w2 and also any biases if you add those). You’ll then update your weights using some update rule which is usually just multiplying the weight gradients by the learning rate (usually denoted alpha).

Is any of this helpful? Which bit do you still not understand?

Thank you that was helpful