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- | ====CS501r, Fall 2018 - Deep Learning: Theory and Practice==== | ||
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- | [[cs501r_f2016:desc|Here is the course description.]] | ||
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- | [[https://www.dropbox.com/sh/cuf3f6py5smk0wg/AACO4aoZaj05UsniFfxQL1gCa?dl=0|All of the slides are posted on Dropbox here]] | ||
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- | ---- | ||
- | === Labs === | ||
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- | [[cs501r_f2018:lab1|Lab 1 - Colab and playground screenshot]] | ||
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- | [[cs501r_f2018:lab2|Lab 2 - Get to know pytorch]] | ||
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- | [[cs501r_f2018:lab3|Lab 3 - Your first DNN]] | ||
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- | [[cs501r_f2018:lab4|Lab 4 - Cancer Detection]] | ||
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- | [[cs501r_f2018:lab5|Lab 5 - Style Transfer]] | ||
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- | [[cs501r_f2018:lab6 | Lab 6 - Unreasonable Effectiveness of RNNs]] | ||
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- | [[cs501r_f2018:lab7 | Lab 7 - Attention Is All You Need]] | ||
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- | [[cs501r_f2018:lab8 | Lab 8 - Improved Wasserstein GAN]] | ||
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- | [[cs501r_f2018:lab9 | Lab 9 - Deep RL & PPO]] | ||
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- | ...More labs will be added here... | ||
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- | [[cs501r_f2016:fp|Final project]] | ||
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- | ---- | ||
- | === Resources === | ||
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- | [[https://pytorch.org/tutorials/|Pytorch tutorials]] | ||
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- | [[https://colab.research.google.com/drive/1TzaPS3jvRadN-URLbQ9nD1ZNoZktfNRy|A good colab tutorial notebook]] | ||
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- | [[supercomputer|A quick intro to deep learning on the supercomputer]] | ||
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- | [[googlecloud|A quick intro to deep learning on google cloud]] | ||
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- | [[http://cs231n.github.io/python-numpy-tutorial/|A great tutorial on python / numpy!]] | ||
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- | ---- | ||
- | === Older stuff === | ||
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- | [[cs501r_f2016:openlabtf|Some instructions for getting Tensorflow to run on the CS open labs]] | ||
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- | [[https://medium.com/xtrememl/why-how-to-use-windows-10-wsl-built-in-linux-for-machine-learning-6a225f4bbd3a|A nice tutorial on setting up wsl for machine learning]] | ||
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- | [[cs501r_f2016:lab_notes|General notes on ipython and seaborn]] | ||