PyTorch Datasets and DataLoaders - Training Set Exploration for Deep Learning and AI

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Exploring and preparing data for neural network programming with PyTorch. We explore our training set, show images on a plot, and touch on oversampling.

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[sulemanrasheed]

The reason for using plt.imshow(np.transpose(grid, (1, 2, 0))):
For a colored image... plt.imshow takes image dimension in following form [height width channels] ...while pytorch follows [channels height width]... so for compatibility we have to change pytorch dimensions so that channels appear at end... the standard representation of array is [axis0 axis1 axis2].... so we have to convert (0, 1, 2) to (1, 2, 0) form to make it compatible for imshow....

[sihanchen]

This series is awesome so far, don't why there are not many people watching it.

[brainify]

Best Explanation bro!!!. Video quality and the way you show typing and then you explain is also just awesome

[simoneparvizi]

OK ok ok ok. Wait a sec. WHY THE FUCK does this extremely well made video (deep explanations, step by step, great audio, great references to Jeremy Howard, to the paper briefely mentioned) got only 50k jesus christ what an amazing video. Ty guys for the awesome work

[chronicfantastic]

That's an interesting point about the effectiveness of oversampling - we had a similar issue with an very unbalanced dataset at work and the sklearn weight-parameter didn't seem to make much difference. It's nice to see some research on it.

[drevolan]

This video would've been amazingly useful last week when I struggled implementing my own DataLoaders/Sets :D
There's not much information about this online so it's greatly appreciated.

But please, normalize your audio, I had to crank my volume to be able to understand what was being said.

But nonetheless good job, these videos are really appreciated.

[JimmyCheng]

volume can be louder. Anxiously waiting for the next episode! Ending is magnificent!

[dippatel]

please keep making video. your content is great.

[yeahorightbro]

Best on you tube. Well done and thank you. Wondering though if you'll do one for custom text datasets?

[picumtg]

Note that the new root should be ./data as it was changed in the fashionmnist

[malamals]

This video series gave me so much insight into deep learning. Thank you Deeplizard team for this amazing work.

Can someone share the video of the paper being used here?

[amitchaudhary]

np.transpose(grid, (1, 2, 0)) can be done in pytorch itself with grid.permute(1, 2, 0)

[panchajanya]

while I was doing on my own, label was not a tensor rather it was an int object.

[xiangli]

can you do a series like this for the custom dataset, thanks?

[xdcedar]

how! could you type so fast and precisely! or does the truth is I am typing too slow actually..

[TheAnubhav]

How do i create batches for custom datasets(non-image data) that are not part of the torchvision package? Is there any resource to learn that?

[zhengguanwang]

Do you have tutorial of hyperparameters for RNN.? That would be great!!!!

[sinaasadiyan]

Hi thanks for your videos.
which version of pytorch are you using in these videos?

[SamerSallam]

Thank u very much for your great series
I guess in the blog article you missed to add image, label = sample

[yunhuaji]

Is that how fast & accurately you normally type codes or just a speeded replay?