PyTorch Tutorial 04 - Backpropagation - Theory With Example

Thank you so much for your extraordinary explanation. Please keep up this informative video.

the best video i could've ever find! thanksss!

First time I finally understand the chain rule in detail....thx!

thankyou for the explanation

The best so far

Strange it makes you disable gradients with no_grad() in order to actually subtract them. The software doing the calculus for you makes it much easier than writing the code manually in C++.

why the calculation of d (y_pred - y)/d y_pred = 1 why not -1 ?

great video! the only thing complicated is this guys "1".

c == z in your video:D

your one dosent seem to be a one...it seems like a big lamda... please try to correct it

thanks, How simple everything is when I hear you draw pictures with a pen and explain

I have installed torch in my system. But in VS code, it shows "No module named torch". If i create virtual env and then pip install torch, it works. But Not In VS Code.
Please help
Thanks

It was Brilliant can you please add playlist for Pytorch with NLP

Da hast du mich wirklich an die Hand genommen und alles ganz super erklärt! danke schön!

Thank you so much (T^T), it made me understand.

It could be better with proper naming

This is wonderful. I appreciate the simple example and translating to PyTorch. Too few videos connect the two. Thank you!