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start [2020/04/24 18:07]
anderson [April]
start [2020/06/25 10:41] (current)
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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 1:\\ Jan 21, 23  | Overview of course, kinds of machine learning, python, jupyter notebooks. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​01 Course Overview.ipynb|01 Course Overview]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​01a Matrix Multiplication on GPU.ipynb|01a Matrix Multplication on GPU]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​02 Matrices and Plotting.ipynb|02 Matrices and Plotting]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​03 Linear Regression with SGD.ipynb|03 Linear Regression with SGD]]  |+| Week 1:\\ Jan 21, 23  | Overview of course, kinds of machine learning, python, jupyter notebooks. ​ | [[https://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​01 Course Overview.ipynb|01 Course Overview]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​01a Matrix Multiplication on GPU.ipynb|01a Matrix Multplication on GPU]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​02 Matrices and Plotting.ipynb|02 Matrices and Plotting]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​03 Linear Regression with SGD.ipynb|03 Linear Regression with SGD]]  |
 | Week 2:\\ Jan 28, 30  | Supervised learning. Linear and nonlinear regression with artificial neural networks. ​  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​04 Linear Regression with Fixed Nonlinear Features.ipynb|04 Linear Regression with Fixed Nonlinear Features]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​05 Introduction to Neural Networks.ipynb|05 Introduction to Neural Networks]] ​ | | Week 2:\\ Jan 28, 30  | Supervised learning. Linear and nonlinear regression with artificial neural networks. ​  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​04 Linear Regression with Fixed Nonlinear Features.ipynb|04 Linear Regression with Fixed Nonlinear Features]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​05 Introduction to Neural Networks.ipynb|05 Introduction to Neural Networks]] ​ |
  
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 | Week 12:\\ Apr 14, 16  | 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 Learning: An 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 12:\\ Apr 14, 16  | 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 Learning: An 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  | Reinforcement learning. History 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 13:\\ Apr 21, 23  | Reinforcement learning. History 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  | Decision TreesRandom ForestsSupport Vector MachinesEnsembles | | | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A6 Tic Tac Toe.ipynb|A6 Tic Tac Toe]] due Friday May 1st by 10:00 PM.   |+| 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 | | |  A7  |+| 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  |  |  | [[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.  | | 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.  |
  
  
  
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