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cs501r_f2018 [2018/08/23 20:01]
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cs501r_f2018 [2021/06/30 23:42] (current)
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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 Anaconda and playground screenshot]]+[[cs501r_f2018:lab6 | Lab Unreasonable Effectiveness of RNNs]]
  
-[[cs501r_f2016:lab2|Lab Perceptron]]+[[cs501r_f2018:lab7 | Lab Attention Is All You Need]]
  
-[[cs501r_f2016:lab3|Lab Gradient descent]]+[[cs501r_f2018:lab8 | Lab Improved Wasserstein GAN]]
  
-[[cs501r_f2017:lab04|Lab Get to know tensorflow]]+[[cs501r_f2018:lab9 | Lab 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]]
  
cs501r_f2018.1535054482.txt.gz · Last modified: 2021/06/30 23:40 (external edit)