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 ===== Announcements ===== ===== Announcements =====
  
-Sept 7:  Assignment 2 is now complete. 
  
-Aug 31: Assignment 1 now includes another example. +Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https://​colostate.instructure.com/​courses/​68135/​external_tools/​2755|Echo 360]].
- +
- +
-Lecture videos are available from the Canvas site (in the menu on the left) by selecting [[https://​colostate.instructure.com/​courses/​55296/​external_tools/​2755|Echo 360]].+
  
 To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file: To use jupyter notebooks on our CS department machines, you must add this line to your .bashrc file:
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   export PATH=/​usr/​local/​anaconda/​bin:​$PATH   export PATH=/​usr/​local/​anaconda/​bin:​$PATH
  
-/* + 
-are available at this [[https://​echo.colostate.edu/​ess/​portal/​section/​a5759ae3-82dc-43df-b515-dd944a6c4976|CS480 video recordings site]]. +This is a tentative schedule of CS440 topics for Fall, 2018 This will be updated during the summer and as the fall semester continues.
-*/+
  
  
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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:\\  Aug 21 - Aug 25    | What is AI?  Promises and fears.\\ Python review.\\ Problem-Solving Agents. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​01 Introduction to AI.ipynb|01 Introduction to AI]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​02 Introduction to Python.ipynb|02 Introduction to Python]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​03 Problem-Solving Agents.ipynb|03 Problem-Solving Agents]]   | Chapters 1, 2, 3.1.\\ [[http://​science.sciencemag.org/​content/​357/​6346/​7.full|AI,​ People, and Society]], by Eric Horvitz.\\ [[https://​aeon.co/​essays/​can-we-design-machines-to-make-ethical-decisions|Automated Ethics]], by Tom Chatfield.\\ [[http://​www.nytimes.com/​2016/​12/​14/​magazine/​the-great-ai-awakening.html?​_r=0|The Great A.I. Awakening]],​ by Gideon Lewis-Krause,​ NYT, Dec 14, 2016.\\ [[https://​www.commondreams.org/​news/​2017/​07/​19/​fundamental-existential-threat-lawmakers-warned-risks-killer-robots|"​Fundamental Existential Threat":​ Lawmakers Warned of the Risks of Killer Robots]], by Julia Conley\\ Section 1 of [[http://​www.scipy-lectures.org|Scipy Lecture Notes]] ​  ​| ​ |  +| Week 1:\\  Aug 20 - Aug 24    | What is AI?  Promises and fears.\\ Python review.\\ Problem-Solving Agents. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​01 Introduction to AI.ipynb|01 Introduction to AI]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​02 Introduction to Python.ipynb|02 Introduction to Python]] ​  | Chapters 1, 2, 3.1 of Russell and Norvig.\\ [[http://​science.sciencemag.org/​content/​357/​6346/​7.full|AI,​ People, and Society]], by Eric Horvitz.\\ [[https://​aeon.co/​essays/​can-we-design-machines-to-make-ethical-decisions|Automated Ethics]], by Tom Chatfield.\\ [[http://​www.nytimes.com/​2016/​12/​14/​magazine/​the-great-ai-awakening.html?​_r=0|The Great A.I. Awakening]],​ by Gideon Lewis-Krause,​ NYT, Dec 14, 2016.\\ [[https://​www.commondreams.org/​news/​2017/​07/​19/​fundamental-existential-threat-lawmakers-warned-risks-killer-robots|"​Fundamental Existential Threat":​ Lawmakers Warned of the Risks of Killer Robots]], by Julia Conley\\ Section 1 of [[http://​www.scipy-lectures.org|Scipy Lecture Notes]] ​  ​| ​ |  
-| Week 2:\\ Aug 28 Sept 1    | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. ​  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​04 Measuring Search Performance.ipynb|04 Measuring Search Performance]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​05 Iterative Deepening and Other Uninformed Search Methods.ipynb|05 Iterative Deepening and Other Uninformed Search Methods]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​06 Python Implementation of Iterative Deepening.ipynb|06 Python Implementation of Iterative Deepening]] ​   | Sections 3.1 - 3.4  |   ​| ​+| Week 2:\\ Aug 27 Aug 31    | Problem-solving search and how to measure performance.\\ Iterative deepening and other uninformed search methods. ​  ​| ​ ​[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​03 Problem-Solving Agents.ipynb|03 Problem-Solving Agents]]\\  ​[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​04 Measuring Search Performance.ipynb|04 Measuring Search Performance]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​05 Iterative Deepening and Other Uninformed Search Methods.ipynb|05 Iterative Deepening and Other Uninformed Search Methods]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​06 Python Implementation of Iterative Deepening.ipynb|06 Python Implementation of Iterative Deepening]] ​   | Sections 3.1 - 3.4 of Russell and Norvig ​ ​| ​  ​| ​
  
  
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 ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^ ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^
-| Week 3:\\ Sept 4 - Sept  | Informed search. A* search. Python classes, sorting, numpy arrays. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​07 Informed Search.ipynb|07 Informed Search]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​08 Python Classes.ipynb|08 Python Classes]]  ​| Rest of Chapter 3  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A1 Uninformed Search.ipynb|A1 Uninformed Search]] due TuesdaySeptember 5that 10:00 PM.\\ Here are examples of good A1 notebooks: ​[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones/A1-good-a.ipynb|a]], [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones/​A1-good-b.ipynb|b]], [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones/​A1-good-c.ipynb|c]][[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones/​A1-good-d.ipynb|d]][[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones/​A1-good-e.ipynb|e]], [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones/​A1-good-f.ipynb|f]][[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones/​A1-good-g.ipynb|g]]  | +| Week 3:\\ Sept 4 - Sept 7\\ No class on the Sept 3 (University Holiday) and Sept 5(instructor traveling). Sept 7 is optional. GTAs will answer assignment questions. ​ | Informed search. A* search. Python classes, sorting, numpy arrays. ​ |   ​| Rest of Chapter 3  |  [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A1 Uninformed Search.ipynb|A1 Uninformed Search]] due FridaySept. 7, 10:00 PM.  Submit your notebook in Canvas.\\ Here are [[http://​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones|good solutions from your classmates]]  | 
-| Week 4:\\ Sept 11 - Sept 15   | A* optimality, admissible heuristics, effective branching factor.\\ Local search and optimization. ​ |[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​09 Heuristic Functions.ipynb|09 Heuristic Functions]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​10 Local Search.ipynb|10 Local Search]] ​ | Chapter 4  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A2 Iterative-Deepening Search.ipynb|A2 Iterative-Deepening Search]] due ThursdaySeptember 14that 10:00 PM.\\ [[http://​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A2answer.tar|A2answer.tar]]   | +| Week 4:\\ Sept 10 Sept 14   Informed searchA* searchPython classessorting, numpy arraysA* optimalityadmissible heuristics, effective branching factor.\\ Local search and optimization | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​07 Informed Search.ipynb|07 Informed Search]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​08 Python Classes.ipynb|08 Python Classes]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​09 Heuristic Functions.ipynb|09 Heuristic Functions]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​10 Local Search.ipynb|10 Local Search]] ​ | Chapter 4  |  [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A2 Iterative-Deepening Search.ipynb|A2 Iterative-Deepening Search]] due FridaySept. 14, 10:00 PM.  Submit your notebook in Canvas.\\ Here are [[http://​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​goodones|good solutions from your classmates]]   | 
-| Week 5:\\ Sept 18 - Sept 22   | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​11 Adversarial Search.ipynb|11 Adversarial Search]] | Chapter 5  | +| Week 5:\\ Sept 17 - Sept 21   | Adversarial search. Minimax. Alpha-beta pruning. Stochastic games. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​11 Adversarial Search.ipynb|11 Adversarial Search]] | Chapter 5  | 
-| Week 6:\\ Sept 25 - Sept 29   | Negamax, with pruning. | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​12 Negamax.ipynb|12 Negamax]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​13 Modern Game Playing.ipynb|13 Modern Game Playing]] ​   |   | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A3 A*, IDS, and Effective Branching Factor.ipynb|A3 A*, IDS, and Effective Branching Factor]] due FridaySeptember 29that 10:00 PM.   |+| Week 6:\\ Sept 24 - Sept 28   | Negamax, with pruning. ​Introduction to Reinforcement Learning.  ​| [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​12 Negamax.ipynb|12 Negamax]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​13 Modern Game Playing.ipynb|13 Modern Game Playing]]\\  [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​14 Introduction to Reinforcement Learning.ipynb|14 Introduction to Reinforcement Learning]] ​      | Chapter 21\\ [[http://​incompleteideas.net/​book/​bookdraft2017nov5.pdf|Reinforcement Learning: An Introduction]] ​  |  [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A3 A*, IDS, and Effective Branching Factor.ipynb|A3 A*, IDS, and Effective Branching Factor]] due WednesdaySept. 26, 10:00 PM.  Submit your notebook in Canvas.   |
  
 ===== October ===== ===== October =====
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 ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^ ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^
-| Week 7:\\ Oct - Oct  ​| ​Introduction to Reinforcement Learning. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​14 Introduction to Reinforcement Learning.ipynb|14 Introduction to Reinforcement Learning]] ​  | Chapter 21\\ [[http://​incompleteideas.net/sutton/book/the-book-2nd.html|Reinforcement Learning: An Introduction]] ​ |  | +| Week 7:\\ Oct - Oct  | Reinforcement Learning ​for Two-Player Games.  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​14 Introduction to Reinforcement Learning.ipynb|14 Introduction to Reinforcement Learning]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​15 Reinforcement Learning for Two-Player Games.ipynb|15 Reinforcement Learning for Two-Player Games]]   | Chapter 21\\ [[http://​incompleteideas.net/​book/​bookdraft2017nov5.pdf|Reinforcement Learning: An Introduction]] ​ |  | 
-| Week 8:\\ Oct - Oct 13  ​| ​Reinforcement Learning for Two-Player Games.\\ ​Introduction to Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​15 Reinforcement Learning for Two-Player Games.ipynb|15 Reinforcement Learning for Two-Player Games]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​16 Introduction to Neural Networks.ipynb|16 Introduction to Neural Networks]] ​ | Sections 18.6 and 18.7  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A4 Negamax with Alpha-Beta Pruning and Iterative Deepening.ipynb|A4 Negamax with Alpha-Beta Pruning and Iterative Deepening]] due Wednesday, October 11th, at 10:00 PM.  ​+| Week 8:\\ Oct - Oct 12  | Introduction to Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​16 Introduction to Neural Networks.ipynb|16 Introduction to Neural Networks]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​17 More Introduction to Neural Networks.ipynb|17 More Introduction to Neural Networks]] ​ | Sections 18.6 and 18.7  |   ​
-| Week 9:\\ Oct 16 - Oct 20  | More Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​17 More Introduction to Neural Networks.ipynb|17 More Introduction to Neural Networks]] ​ | +| Week 9:\\ Oct 15 - Oct 19  | More Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​17 More Introduction to Neural Networks.ipynb|17 More Introduction to Neural Networks]] ​ | 
-| Week 10:\\ Oct 23 - Oct 27  | Introduction to Classification. Bayes Rule. Generative versus Discriminative. Linear Logistic Regression. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​18 Introduction to Classification.ipynb|18 Introduction to Classification]] ​  ​| ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A5 Reinforcement Learning Solution to Towers of Hanoi.ipynb|A5 Reinforcement Learning Solution to Towers of Hanoi]] due WednesdayOctober 25that 10:00 PM.  |+| Week 10:\\ Oct 22 - Oct 26  | Introduction to Classification. Bayes Rule. Generative versus Discriminative. Linear Logistic Regression. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​18 Introduction to Classification.ipynb|18 Introduction to Classification]] ​  ​| ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A4 Reinforcement Learning Solution to Towers of Hanoi.ipynb|A4 Reinforcement Learning Solution to Towers of Hanoi]] due MondayOct. 22, 10:00 PM.  ​Submit your notebook in Canvas. ​  ​| ​ |
  
 ===== November ===== ===== November =====
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 ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^ ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^
-| Week 11:\\ Oct 30 - Nov  | Classification with Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​19 Classification with Linear Logistic Regression.ipynb|19 Classification with Linear Logistic Regression]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​20 Classification with Nonlinear Logistic Regression Using Neural Networks.ipynb|20 Classification with Nonlinear Logistic Regression Using Neural Networks]] ​ | |[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​Project Proposal.ipynb|Project Proposal]] due Wednesday, November 1st, at 10:00 PM. +| Week 11:\\ Oct 29 - Nov  | Classification with Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​19 Classification with Linear Logistic Regression.ipynb|19 Classification with Linear Logistic Regression]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​20 Classification with Nonlinear Logistic Regression Using Neural Networks.ipynb|20 Classification with Nonlinear Logistic Regression Using Neural Networks]] ​ | | | 
-| Week 12:\\ Nov - Nov 10  | Reinforcement Learning with Neural Networks.\\ Lecture and Chuck'​s office hours on Thursday are <color red>​cancelled</​color>​. ​ He will be out of town.  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​21 Reinforcement Learning with a Neural Network as the Q Function.ipynb|21 Reinforcement Learning with a Neural Network as the Q Function]] ​ |  | +| Week 12:\\ Nov - Nov  | Reinforcement Learning with Neural Networks. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​21 Reinforcement Learning with a Neural Network as the Q Function.ipynb|21 Reinforcement Learning with a Neural Network as the Q Function]] ​ | | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​Project Proposal.ipynb|Project Proposal]] due Wednesday, November 7th, at 10:00 PM.   | 
-| Week 13:\\ Nov 13 - Nov 17  | Faster Reinforcement Learning. Autoencoder neural networks.  ​| [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​22 Autoencoder Neural Networks.ipynb|22 Autoencoder Neural Networks]]  |  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​A6 Neural Networks.ipynb|A6 Neural Networks]] ​due <color red>​Friday,​ November 17th, at 10:00 PM.</​color> ​ | +| Week 13:\\ Nov 12 - Nov 16  ​| ​Faster Reinforcement Learning. Autoencoder neural networks. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​22 Autoencoder ​Neural Networks.ipynb|22 Autoencoder ​Neural Networks]] ​ ​| ​ |  | 
-|  Nov 20 - Nov 24  ​| ​ Fall Break  | +|  Nov 19 - Nov 23  ​| ​ Fall Recess ​ | 
-| Week 14:\\ Nov 27 Dec 1  | Constraint satisfaction. Min-conflicts ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​23 Constraint Satisfaction Problems.ipynb|23 Constraint Satisfaction Problems]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​24 Min-Conflicts in Python with Examples.ipynb|24 Min-Conflicts in Python with Examples]] ​ | Chapter 6.\\ [[http://​dl.acm.org/​citation.cfm?​id=1928809|A new iterated local search algorithm for solving broadcast scheduling problems in packet radio networks]] ​ | +| Week 14:\\ Nov 26 Nov 30  | Constraint satisfaction. Min-conflicts ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​23 Constraint Satisfaction Problems.ipynb|23 Constraint Satisfaction Problems]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​24 Min-Conflicts in Python with Examples.ipynb|24 Min-Conflicts in Python with Examples]] ​ | Chapter 6.\\ [[http://​dl.acm.org/​citation.cfm?​id=1928809|A new iterated local search algorithm for solving broadcast scheduling problems in packet radio networks]] ​ | 
  
 ===== December ===== ===== December =====
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 ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^ ^  Week      ^  Topic      ^  Material ​ ^  Reading ​         ^  Assignments ​ ^
-| Week 15:\\ Dec - Dec  | Recurrent neural networks and use in natural language\\ <color ref>Dec 7, Thursday, PLEASE ATTENDCourse Surveys will be filled out.</color>  ​ |   |  +| Week 15:\\ Dec - Dec  | Recurrent neural networks and use in natural language ​ | [[http://​nbviewer.ipython.org/url/​www.cs.colostate.edu/​~anderson/​cs440/​notebooks/​25 Natural Language.ipynb|25 Natural Language]] ​|   |  
-Finals ​Week:\\ Dec 11 - Dec 15  ​| ​  ​| ​ | | Final Project notebook is due Tuesday, Dec 12th, 10:00 pm.  |+Final Exam Week:\\ Dec 10 - Dec 14  ​| ​  ​| ​ | | Final Project notebook is due Tuesday, Dec 11th, 10:00 pm.   ​|
  
  
  
start.1512419493.txt.gz · Last modified: 2017/12/04 13:31 by anderson