Diving Deep into PyTorch

Part 2 (2019)
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I’ve been working a series of tutorials called PyTorch: Zero to GANs, inspired from the FastAI development notebooks. The first 3 tutorials are live at the moment:

  1. PyTorch Basics: Tensors & Gradients
  2. Linear Regression and Gradient Descent
  3. Image Classification using Logistic Regression
  4. more coming soon (CNNs, RNNs, GANs etc.)

With some help from the Bangalore study group, we are also planning to conduct workshops and put the recordings online. I hope this will be useful resource for learning PyTorch in depth.

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Thank you @aakashns! I am sure that these would be wonderful references for many people.

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If you are familiar with Numpy, you might find this one-to-one comparison of Numpy functions to PyTorch functions helpful.

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This is an excellent tutorial, @aakashns! Thank you!

Except it has a very convoluted setup (which as I pointed out in the comment on medium doesn’t work on linux w/o fixing the conda env file). Suggestions to make it more accessible to more people:

  • it could just say conda install pytorch torchvision -c pytorch
  • if you do continue with the setup you have now you first need to tell the user to quit the currently activated conda env, conda activate base otherwise what a mess it creates!
  • github repo would have been a lot easier to keep up with updates and being able to submit corrections.
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This one is well designed too: http://deeplizard.com/learn/video/v5cngxo4mIg
But it has been sitting there for a few months now without continuation, incomplete… but things are explained quite well.

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I found this tutorial useful: https://www.youtube.com/watch?v=_H3aw6wkCv0

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With our local learning community we are currently going through part 1 and look deeper into PyTorch. For that we set up a repo which could be of interest for others:


Currently, we just started with lesson 1 and we will expand it with information and notebooks as we move along. So far you will find there a lot of very good PyTorch resources to get going.

We will also update it to include the great material posted in this thread!
Thank you all for the contributions!

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This is wonderful! I am sure that it will be super helpful to many people. Could you please find a place to put it in the top post?

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The deeplizard PyTorch series is really good. I can’t recommend it enough. It’s short, but the guy is an amazing teacher.

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Sounds great – could you please provide the URL?

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Somehow this one is still missing in this thread (it‘s mentioned in others here on the forum though), a free udacity course by the makers of pytorch (facebook ai) on dl with pytorch, I found this to be pretty good! Includes sections you can probably skip depending on your level and non core sections like an interview with Soumith, but I can definitely recommend it.

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I do agree it’s a very nice course.

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stas provided one above, but here’s the link to the youtube playlist https://www.youtube.com/watch?v=v5cngxo4mIg&list=PLZbbT5o_s2xrfNyHZsM6ufI0iZENK9xgG

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Oh, please feel free to add it in the top post wherever you find appropriate. It is wikified so we all can edit. I am sure that it is a wonderful class.

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Found someone’s notes from that audacity course (apparently only first 2 parts):

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In case it is useful for someone, here is a PyTorch tutorial that I wrote: https://nbviewer.jupyter.org/github/joshfp/pytorch-from-dummy-to-sota/blob/master/pytorch-from-dummy-to-sota.ipynb

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Of course it is useful!

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Thanks for putting this together!
For those in the Bay area, I’m suggesting a study group and I’m thinking to do a Deep Dive into PyTorch in parallel with the normal lessons - if anybody is interested: https://forums.fast.ai/t/study-group-in-sf-berkeley/41461

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Great idea! Wish you success!

Feel free to put the announcement in the top post!

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You can currently get the ebook “Deep Learning with PyTorch - Essential Excerpts” for free from the Pytorch website: https://pytorch.org/deep-learning-with-pytorch

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