PyTorch Course (2022), Part 4: Image Classification (MNIST)

In this video we use the network constructed in the previous video to train a neural network on the MNIST data set. The goal of this network is to take in images of hand written digits, and predict what digit they correspond to.

Code:

MNIST Data

Discord:

PyTorch website:

[lomash_irl]

What a hidden gem! This video isn't just about image classification, it also explains how to use datasets, dataloaders, and create training functions, step by step. I highly recommend watching the first video in this series on tensors.

[panoskotoulas]

That's a great series. Seeing both theory and practice at the same time is awesome and makes it easier to understand the process. Really hope you'll continue the series. I know it's too much work for little views but I people really benefit from watching these videos, they're top quality.

[rankinstudio]

Hey man. Just wanted to say thanks. After watching this about 100x I was able to successfully build my own image dataset and get this working. Great tutorial, and excellent explanations. Looking forward to another installment and hearing more about your research. Cheers

[cianjones]

I find this series amazing. You're a very good teacher! Are you planning on continuing this series in the future?

[Iwillseeyouagaininyears]

Great series!

In case anyone in the future has a problem as me:
If you run into the error message

cannot import name 'PILLOW_VERSION' from 'PIL'

when importing torchvision, update torchvision to a version >=0.5.0. Alternatively, downgrade pillow < version 7.
Pillow changed 'PILLOW_VERSION'' to '__version__'.

[shots]

Please continue whenever you get time out of your busy schedule sire!

[cvicracer]

Your explanation is very easy to follow, thank you very much.

[DEEPAKSV]

Your teaching is so good!! You really deserve way more views & subscribers. I was able to find this tutorial series since I specifically searched for a Pytorch tutorial with the latest version. Wonder why doesn't the youtube algorithm put your video at the top.

Also would you consider making a Part-5 of this series on building CNN with Pytorch?

[kaba]

Wow I was thinking why we're using vectors in programming
Thanks great video

[oludelehalleluyah]

You've stopped this series.

I am enjoying it.

[jakstrike]

Top vids! Got hooked on the memes but this is good pytorch intro content too coming from tabular data ML background.

[rishidixit]

At 24:00 when reshaping isn’t the row major order going to affect how rows are made from the original data ?

[propjoe]

My go-to channel when I need the basics of NN💯🎉. Please can make a playlist on CNN and RNN.

[yamanarslanca]

Thanks for the video. Around @4:00 you used one-hot encoding and I understand the concept. But I wonder a case where you had too many categorical data (for example 100 different numbers in your target) so your num_classes would be higher than 10 (a lot higher). Then if you apply one-hot encoding in this case you would increase your feature space dramatically and I assume this would lead to "curse of dimensionality" or something similar that which makes your model's performance worse. Do you know how to deal with such situation ?

Also, I know this is a noob question but I just want to be sure, when you initialize your model (model=ModelClass()) initial parameters of the model (initial weights and bias) is automatically and randomly assigned by the -torch.nn.Module- or by optimization function -SGD(f.parameters())- ?

Thanks.

[qualimania]

Hey, great tutorial! I have a question regarding the dataset. For some reason, the link you provided is not working. I wonder if someone else has the same problem. Any help will be appreciated!

[aliabasnezhad]

Can you explain, when defining CTDataset, why you didn't use super? Thanks!

[mrmkl]

If I increase my batch size the predictions (and the loss) gets worse and worse. Why can that be the case?

[ИванСергиенко-бз]

thank you very much for your tutorial. it's very useful. Could you pls explain, how can i test this model with random img? problem is that img.shape is ([28, 28, 3]) with color channel. how can i remove 3d dimension?

[HimanshuGauttam]

The given code segment


L(f(xs), ys) (line number 63) produces the error message.
RuntimeError: 1D target tensor expected, multi-target not supported

[himanshuchaudhary]

I had been trying to contact with you, I am working on few project in Cosmology. I want to to regarding about those topic