Obviously this is a year old and the narrator probably won't see this but a zoomed in view would make this infinitely more accessible on mobile. Great video regardless.
The colors make it really hard to read the slides
I found this helpful. Thanks for sharing this tutorial! I found a problem in the Autograd section, which could be corrected. I'm using Pytorch2.1.1 and it seems that `loss.backdward()` requires that the tensors get constructed with `requires_grad=True`. I checked the documentation and it seems that this is the default, but it didn't work for me until I specified the value explicitly.
It really help a lot!😀
nice "how to read the text" tutorial!
Thank you for the video
Very hard to read the slide due to unfortunate choices of font colors (no contrast)
I think in code segment 6 the first line should be r1 = (torch.rand(2,2)-0.5) * 2 otherwise it will be equivalent to r1 = torch.rand(2,2) - 1
Is there a typo ~ 15:10 when the image normalization is done? if we're seeking to achieve an average of 0, shouldn't the first tuple passed in be (0, 0, 0) instead of (0.5, 0.5, 0.5)?
loss.backward() does not compute at 9:42 lol
Audio volume is a bit low.
Is it just my machine, or is this video kinda dark?
Great video! Thank you. Just a quick question, shouldn't the add node be connected to the h2h and i2h nodes instead of the MM nodes?
good videos but audio quality in these videos is very poor, anyway to improve it?
16:54 I get an error on dataiter.next() - next(dataiter) works
useful
Does PyTorch have something equivalent to TensorFlow Probability?
Am I the only one that feels the display brightness is too low?
HI, I get this error when runnung the dataset notebook. "URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: certificate has expired (_ssl.c:1123)>" Can it be fixed?
@niyongaboeric