User Tools

Site Tools


start

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision
Previous revision
Next revision Both sides next revision
start [2018/10/22 10:10]
127.0.0.1 external edit
start [2018/11/07 17:36]
127.0.0.1 external edit
Line 37: Line 37:
 | Week 7:\\ Oct 1 - Oct 5  | 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 7:\\ Oct 1 - Oct 5  | 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 8 - 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 8:\\ Oct 8 - 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 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 9:\\ Oct 15 - Oct 19  | More Neural Networks. Autoencoders.  | [[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]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/22 Autoencoder Neural Networks.ipynb|22 Autoencoder Neural Networks]]  |
 | 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 Monday, Oct. 22, 10:00 PM.  Submit your notebook in Canvas.    | | 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 Monday, Oct. 22, 10:00 PM.  Submit your notebook in Canvas.    |
  
Line 44: Line 44:
 |< 100% 10% 20% 30% 20% 20%  >| |< 100% 10% 20% 30% 20% 20%  >|
 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 11:\\ Oct 29 - Nov 2  | 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/A5 Neural Networks.ipynb|A5 Neural Networks]] due Friday, Nov. 2, 10:00 PM.  | +| Week 11:\\ Oct 29 - Nov 2  | Classification with Neural Networks. Reinforcement Learning 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/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 5 - Nov 9  | 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 FridayNovember 9that 10:00 PM.   | +| Week 12:\\ Nov 5 - Nov 9  | Introduction to Pytorch.\\ Constraint satisfaction.\\ Min-conflicts.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/23 Introduction to Pytorch.ipynb|23 Introduction to Pytorch]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/24 Constraint Satisfaction Problems.ipynb|24 Constraint Satisfaction Problems]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/25 Min-Conflicts in Python with Examples.ipynb|25 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]]  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A5 Neural Networks.ipynb|A5 Neural Networks]] due MondayNov. 5, 10:00 PM.\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/Project Proposal.ipynb|Project Proposal]] due Friday, November 9th, at 10:00 PM.   | 
-| 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]]  |  |  |+| Week 13:\\ Nov 12 - Nov 16  | Faster Reinforcement Learning.  |   |  |  |
 |  Nov 19 - Nov 23  |  Fall Recess  | |  Nov 19 - Nov 23  |  Fall Recess  |
-| 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]]  +| Week 14:\\ Nov 26 - Nov 30  |   |    | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A6 Min-Conflicts.ipynb|A6 Min-Conflicts]] due Monday, Nov26, 10:00 PM  
  
 ===== December ===== ===== December =====
start.txt · Last modified: 2024/01/08 18:40 (external edit)