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- | ====CS501r, Fall 2017 - Deep Learning: Theory and Practice==== | ||
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- | [[cs501r_f2016:desc|Here is the course description.]] | ||
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- | [[http://cs231n.github.io/python-numpy-tutorial/|Remember, this is a great tutorial on python / numpy!]] | ||
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- | [[cs501r_f2016:openlabtf|Some instructions for getting Tensorflow to run on the CS open labs]] | ||
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- | [[https://www.dropbox.com/sh/q4tt30kxxc3mvgs/AABEdP4l7slOA5B1QqOA5HJra?dl=0|All of the slides are posted on Dropbox here]] | ||
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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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- | [[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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- | === Labs === | ||
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- | [[cs501r_f2016:lab_notes|General notes on ipython and seaborn]] | ||
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- | [[cs501r_f2016:lab1|Lab 1 - Anaconda and playground screenshot]] | ||
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- | [[cs501r_f2016:lab2|Lab 2 - Perceptron]] | ||
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- | [[cs501r_f2016:lab3|Lab 3 - Gradient descent]] | ||
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- | [[cs501r_f2017:lab04|Lab 4 - Get to know tensorflow]] | ||
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- | [[cs501r_f2017:lab5v2|Lab 5 - Your first Tensorflow image classifier]] | ||
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- | [[cs501r_f2016:lab6v2|Lab 6 - Cancer detector]] | ||
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- | [[cs501r_f2017:lab7|Lab 7 - Generative adversarial networks]] | ||
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- | [[cs501r_f2016:lab10|Lab 8 - RNNs, LSTMs, GRUs]] | ||
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- | [[cs501r_f2016:lab9|Lab 9 - Siamese networks]] | ||
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- | [[cs501r_f2016:lab13|Lab 10 - Inceptionism / deep art]] | ||
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- | [[cs501r_f2016:lab14|Lab 11 - Neural machine translation]] | ||
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- | [[cs501r_f2016:fp|Final project]] | ||
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- | ====Old labs that we probably won't use==== | ||
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- | [[cs501r_f2016:lab6|Lab 6 - Feature zoo 1]] | ||
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- | [[cs501r_f2016:lab5b|Lab 5b - Convolutional Tensorflow image classifier and Tensorboard]] | ||