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In english:
- Deep learning frameworks - video
- PyTorch tutorial
- Tensorflow tutorial
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In russian:
- Pytorch tutorial recommended
- Tensorflow tutorial (english only for now. Links are welcome)
- A lecture on nonlinearities, intializations and other tricks in deep learning (karpathy) - video
- A lecture on activations, recap of adaptive SGD and dropout (karpathy) - video
- a deep learning neophite cheat sheet
- [bonus video] Deep learning philosophy: our humble take (english)
- [reading] on weight initialization: blog post
- [reading] pretty much all the module 1 of http://cs231n.github.io/
As usual, go to seminar_pytorch.ipynb and follow instructions from there. You will also need to pass homework_pytorch.ipynb for full score.
Alternative (TensorFlow): a similar tutorial for tensorflow is provided in tensorflow.ipynb. From now on, you can submit assignments in any framework - but you will have to do some extra engineering in that case. However, unless you're already profficient with PyTorch, we recommend you stick to it.