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schedule [2020/03/30 10:14]
anderson [April]
schedule [2020/05/08 11:30] (current)
anderson [May]
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 |< 100% 10% 20% 30% 20% 20%  >| |< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^ ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^
-| Week 10:\\ Mar 31, Apr 2  | Convolutional neural networks. Classification with Pytorch and Keras.  | | | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A4.2 Classification of Hand-Drawn Digits.ipynb|A4.2 Classification of Hand-Drawn Digits]] due Thursday, April 2nd, 10:​00PM ​ |  +| Week 10:\\ Mar 31, Apr 2  | Convolutional neural networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​13 Convolutional Neural Networks.ipynb|13 Convolutional Neural Networks]], [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​14 Convolutional Neural Network Training with Numpy.ipynb|14 Convolutional Neural Network Training with Numpy]] ​  | |  |  
-| Week 11:\\ Apr 79   | Introduction to reinforcement learning, ​with discrete state and action using tables and neural networks.  |  +| Week 11:\\ Apr 7, 9   ​| ​Classification with Pytorch. Assignment 5. , with discrete state and action using tables and neural networks.  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​15 Convolutional Neural Networks in Pytorch.ipynb|15 Convolutional Neural Networks in Pytorch]]  ​| | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A4.2 Classification of Hand-Drawn Digits.ipynb|A4.2 Classification of Hand-Drawn Digits]] due Tuesday, April 7th, 10:​00PM ​ | 
-Week 12:\\ Apr 1416  ​| ​Reinforcement learning with continuous state and action.  | +| Week 12:\\ Apr 1416  ​Reinforcement learning. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​16 ​Introduction to Reinforcement Learning.ipynb|16 Introduction to Reinforcement Learning]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​17 Reinforcement Learning ​with Neural Network as Q Function.ipynb|17 Reinforcement Learning with Neural Network as Q Function]] ​ ​| ​ ​[[http://​incompleteideas.net/​book/​the-book.html|Reinforcement LearningAn Introduction]]by Richard Sutton and Andrew Barto, 2nd edition ​ ​| ​[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​Project Proposal.ipynb|Project Proposal]] due Thursday, April 16th, 10:00PM\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A5.4 2-D and 1-D Convolutional Neural Networks in Pytorch.ipynb|A5.4 2-D and 1-D Convolutional Neural Networks in Pytorch]] due Saturday, April 18th, 10:​00PM ​ | 
-| Week 13:\\ Apr 21, 23  | Decision TreesRandom Forests.  | +| Week 13:\\ Apr 21, 23  | Reinforcement learningHistory and future of AI as discussed in [[https://​www.elementai.com/​podcast#​|episode of AI Element Podcast]] ​ ​| ​[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​18.1 Reinforcement Learning to Control a Marble.ipynb|18.1 Reinforcement Learning to Control a Marble]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​19 Reinforcement Learning for Two Player Games.ipynb|19 Reinforcement Learning for Two Player Games]] ​ |     
-| Week 14:\\ Apr 28, 30  | Support Vector MachinesEnsembles.  |+| Week 14:\\ Apr 28, 30  | Linear and Nonlinear Dimensionality Reduction ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​20 Linear Dimensionality Reduction.ipynb|20 Linear Dimensionality Reduction]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​21.1 Nonlinear Dimensionality Reduction with Autoencoder Neural Networks.ipynb|21.1 Nonlinear Dimensionality Reduction with Autoencoder Neural Networks]] ​ | | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A6.2 Tic Tac Toe.ipynb|A6.2 Tic Tac Toe]] due Friday May 1st by 10:00 PM.   |
  
 ===== May ===== ===== May =====
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 |< 100% 10% 20% 30% 20% 20%  >| |< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^ ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^
-| Week 15:\\ May 5, 7  | Unsupervised learning. Clustering, K-Means, PCA, t-SNE.  | +| Week 15:\\ May 5, 7  | Unsupervised learning. Clustering, K-Means ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​22 K-Means Clustering.ipynb|22 K-Means Clustering]] ​  | | [[https://​towardsdatascience.com/​visualizing-covid-19-data-beautifully-in-python-in-5-minutes-or-less-affc361b2c6a|Find data on COVID-19 cases updated daily and display using matplotlib]] ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A7.1 Autoencoder for Classification.ipynb|A7.1 Autoencoder for Classification]] due Friday May 8th by 10:00 PM.    ​
-| May 11 - 15  |  Final Exam Week  |  |  | Final Project Report due Tuesday, May 12, 10:00 PM.  |+| May 11 - 15  |  Final Exam Week  |  |  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​Project Report Example.ipynb|Project Report]] due Tuesday, May 12, 10:00 PM.  |
  
  
  
schedule.1585584847.txt.gz · Last modified: 2020/03/30 10:14 by anderson