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[[cs501r_f2016:desc|Here is the course description.]] | [[cs501r_f2016:desc|Here is the course description.]] | ||
- | [[http://cs231n.github.io/python-numpy-tutorial/|Remember, this is a great tutorial on python / numpy!]] | + | [[https://www.dropbox.com/sh/cuf3f6py5smk0wg/AACO4aoZaj05UsniFfxQL1gCa?dl=0|All of the slides are posted on Dropbox here]] |
- | [[cs501r_f2016:openlabtf|Some instructions for getting Tensorflow to run on the CS open labs]] | + | ---- |
+ | === Labs === | ||
- | [[https://www.dropbox.com/sh/q4tt30kxxc3mvgs/AABEdP4l7slOA5B1QqOA5HJra?dl=0|All of the slides are posted on Dropbox here]] | ||
- | [[supercomputer|A quick intro to deep learning on the supercomputer]] | + | [[cs501r_f2018:lab1|Lab 1 - Colab and playground screenshot]] |
- | [[googlecloud|A quick intro to deep learning on google cloud]] | + | [[cs501r_f2018:lab2|Lab 2 - Get to know pytorch]] |
- | [[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]] | + | [[cs501r_f2018:lab3|Lab 3 - Your first DNN]] |
- | ---- | + | [[cs501r_f2018:lab4|Lab 4 - Cancer Detection]] |
- | === Labs === | + | |
- | [[cs501r_f2016:lab_notes|General notes on ipython and seaborn]] | + | [[cs501r_f2018:lab5|Lab 5 - Style Transfer]] |
- | [[cs501r_f2016:lab1|Lab 1 - Anaconda and playground screenshot]] | + | [[cs501r_f2018:lab6 | Lab 6 - Unreasonable Effectiveness of RNNs]] |
- | [[cs501r_f2016:lab2|Lab 2 - Perceptron]] | + | [[cs501r_f2018:lab7 | Lab 7 - Attention Is All You Need]] |
- | [[cs501r_f2016:lab3|Lab 3 - Gradient descent]] | + | [[cs501r_f2018:lab8 | Lab 8 - Improved Wasserstein GAN]] |
- | [[cs501r_f2017:lab04|Lab 4 - Get to know tensorflow]] | + | [[cs501r_f2018:lab9 | Lab 9 - Deep RL & PPO]] |
- | [[cs501r_f2017:lab5v2|Lab 5 - Your first Tensorflow image classifier]] | + | ...More labs will be added here... |
- | [[cs501r_f2016:lab6v2|Lab 6 - Cancer detector]] | + | [[cs501r_f2016:fp|Final project]] |
- | [[cs501r_f2017:lab7|Lab 7 - Generative adversarial networks]] | ||
- | [[cs501r_f2016:lab10|Lab 8 - RNNs, LSTMs, GRUs]] | + | ---- |
+ | === Resources === | ||
- | [[cs501r_f2016:lab9|Lab 9 - Siamese networks]] | ||
- | [[cs501r_f2016:lab13|Lab 10 - Inceptionism / deep art]] | + | [[https://pytorch.org/tutorials/|Pytorch tutorials]] |
- | [[cs501r_f2016:lab14|Lab 11 - Neural machine translation]] | + | [[https://colab.research.google.com/drive/1TzaPS3jvRadN-URLbQ9nD1ZNoZktfNRy|A good colab tutorial notebook]] |
- | [[cs501r_f2016:fp|Final project]] | + | [[supercomputer|A quick intro to deep learning on the supercomputer]] |
+ | [[googlecloud|A quick intro to deep learning on google cloud]] | ||
- | ====Old labs that we probably won't use==== | ||
- | [[cs501r_f2016:lab6|Lab 6 - Feature zoo 1]] | + | [[http://cs231n.github.io/python-numpy-tutorial/|A great tutorial on python / numpy!]] |
- | [[cs501r_f2016:lab5b|Lab 5b - Convolutional Tensorflow image classifier and Tensorboard]] | + | |
+ | ---- | ||
+ | === Older stuff === | ||
+ | |||
+ | |||
+ | |||
+ | [[cs501r_f2016:openlabtf|Some instructions for getting Tensorflow to run on the CS open labs]] | ||
+ | |||
+ | [[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]] | ||
+ | |||
+ | [[cs501r_f2016:lab_notes|General notes on ipython and seaborn]] | ||