CS440: Introduction to Artificial Intelligence

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start [2017/04/14 08:49]
anderson [May] 		start [2017/05/25 14:15]
anderson [Announcements]
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 ===== Announcements ===== ===== Announcements =====
  
-**March 20:** A4grader.tar linked to on the A4 web page has been updated. It longer checks for QDA-related functions. 
  
-**March 18:** There will be no lecture class on Wednesday, March 22nd.  Chuck's office hours on March 22nd are cancelled.+Lecture videos will be available.
  
-Lecture videos are available at this [[https://echo.colostate.edu/ess/portal/section/a5759ae3-82dc-43df-b515-dd944a6c4976|CS480 video recordings site]].+/* 
 +are available at this [[https://echo.colostate.edu/ess/portal/section/a5759ae3-82dc-43df-b515-dd944a6c4976|CS480 video recordings site]]. 
 +*/
  
  
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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 11:\\ Apr 3 - Apr 7   | Reinforcement Learning.  Two-player games.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/21 Reinforcement Learning for Two Player Games.ipynb|21 Reinforcement Learning for Two Player Games]]   | [[http://incompleteideas.net/sutton/book/the-book-2nd.html| Reinforcement Learning: An Introduction]], by Richard Sutton and Andrew Barto. 2nd edition draft. On-line and free.  |  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A4 Classification with LDA and Logistic Regression.ipynb|A4 Classification with LDA and Logistic Regression]] due Wednesday, April 5th at 10:00 PM.\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/Project Proposal.ipynb|Project Proposal]] due Friday, April 7th at 10:00 PM.  |+| Week 11:\\ Apr 3 - Apr 7   | Reinforcement Learning.  Two-player games.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/21 Reinforcement Learning for Two Player Games.ipynb|21 Reinforcement Learning for Two Player Games]]   | [[http://incompleteideas.net/sutton/book/the-book-2nd.html| Reinforcement Learning: An Introduction]], by Richard Sutton and Andrew Barto. 2nd edition draft. On-line and free.  |  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A4 Classification with LDA and Logistic Regression.ipynb|A4 Classification with LDA and Logistic Regression]] due Wednesday, April 5th at 10:00 PM.\\ Here are [[A4-good-ones|examples of good A4 reports.]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/Project Proposal.ipynb|Project Proposal]] due Friday, April 7th at 10:00 PM.  |
 | Week 12:\\ Apr 10 - Apr 14  | Neural networks as Q functions.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/22 Reinforcement Learning with Neural Network as Q Function.ipynb|22 Reinforcement Learning with Neural Network as Q Function]]\\ [[http://www.cs.colostate.edu/~anderson/cs480/notebooks/17pole.odp|Faster RL by Pre-training]]  | [[https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/|The Dark Secret at the Heart of AI]]\\ [[https://flipboard.com/@flipboard/flip.it%2FVaiyLS-the-tiny-changes-that-can-cause-ai-to-f/f-32bef81237%2Fbbc.com|The Tiny Changes That Can Cause AI to Fail]]  |  | | Week 12:\\ Apr 10 - Apr 14  | Neural networks as Q functions.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/22 Reinforcement Learning with Neural Network as Q Function.ipynb|22 Reinforcement Learning with Neural Network as Q Function]]\\ [[http://www.cs.colostate.edu/~anderson/cs480/notebooks/17pole.odp|Faster RL by Pre-training]]  | [[https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/|The Dark Secret at the Heart of AI]]\\ [[https://flipboard.com/@flipboard/flip.it%2FVaiyLS-the-tiny-changes-that-can-cause-ai-to-f/f-32bef81237%2Fbbc.com|The Tiny Changes That Can Cause AI to Fail]]  |  |
-| Week 13:\\ Apr 17 - Apr 21  |  |  |  |  | +| Week 13:\\ Apr 17 - Apr 21  | Unsupervised Learning. Dimensionality reduction.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/23 Linear Dimensionality Reduction.ipynb|23 Linear Dimensionality Reduction]]\\  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/24 Nonlinear Dimensionality Reduction with Digits Example.ipynb|24 Nonlinear Dimensionality Reduction with Digits Example]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/25 K-Means Clustering.ipynb|25 K-Means Clustering]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/26 Hierarchical Clustering.ipynb|26 Hierarchical Clustering]]   |  |  | 
-| Week 14:\\ Apr 24 - Apr 28  |  |  |  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A5 Control a Marble with Reinforcement Learning.ipynb|A5 Control a Marble with Reinforcement Learning]] due Monday, April 24th at 10:00 PM. |+| Week 14:\\ Apr 24 - Apr 28  | Nonparametric Classification Algorithms  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/27 Nonparametric Classification with K Nearest Neighbors.ipynb|27 Nonparametric Classification with K Nearest Neighbors]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/28 Support Vector Machines.ipynb|28 Support Vector Machines]]  |  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/A5 Control a Marble with Reinforcement Learning.ipynb|A5 Control a Marble with Reinforcement Learning]] due Monday, April 24th at 10:00 PM.\\ Here are [[A5-good-ones|examples of good A5 reports.]] |
  
 ===== 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 1 - May 5   |   |  |  |  | +| Week 15:\\ May 1 - May 5   | Brain-Computer Interfaces.  Ensembles.   | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/29 Machine Learning for Brain-Computer Interfaces.ipynb|29 Machine Learning for Brain-Computer Interfaces]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/30 Comparison of Algorithms for BCI.ipynb|30 Comparison of Algorithms for BCI]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/31 Convolutional Neural Networks for BCI.ipynb|31 Convolutional Neural Networks for BCI]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs480/notebooks/32 Ensembles of Convolutional Neural Networks.ipynb|32 Ensembles of Convolutional Neural Networks]]\\ [[http://www.cs.colostate.edu/~anderson/cs480/notebooks/16harvard.odp|Patterns in EEG for Brain-Computer Interfaces and Recent Results with Tripolar EEG Electrodes]]   |  | Please complete the Course Surveys that are now available on Canvas.  Fill out the survey for your section, either on-campus or distance-learning.  | 
-| Finals Week:\\ May 8 - May 11  |   |  |  |  Final project due Tuesday, May 9, 10:00 PM.  Details on report requirements will be posted here soon.   |+| Finals Week:\\ May 8 - May 11  |   |  |  |  Final project due Tuesday, May 9, 10:00 PM.   [[Final Project Report|Here is a summary]] of what is expected in your reports.   |
  
  
  
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