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start [2020/10/19 09:45]
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start [2020/12/08 14:01]
anderson [December]
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 | Week 7:\\ Oct 5 - Oct 9\\ <color red>Oct 8 Lecture will not meet, but recording will be available.</color>  | Reinforcement Learning for Two-Player Games.  | [[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 5 - Oct 9\\ <color red>Oct 8 Lecture will not meet, but recording will be available.</color>  | Reinforcement Learning for Two-Player Games.  | [[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 12 - Oct 16  | Constraint satisfaction.\\ Min-conflicts.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/16 Constraint Satisfaction Problems.ipynb|16 Constraint Satisfaction Problems]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/17 Min-Conflicts.ipynb|17 Min-Conflicts]]  <!-- \\ [[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  | | Week 8:\\ Oct 12 - Oct 16  | Constraint satisfaction.\\ Min-conflicts.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/16 Constraint Satisfaction Problems.ipynb|16 Constraint Satisfaction Problems]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/17 Min-Conflicts.ipynb|17 Min-Conflicts]]  <!-- \\ [[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  |
-| Week 9:\\ Oct 19 - Oct 23  | Natural language understanding and translation.   <!-- [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/26 Natural Language.ipynb|26 Natural Language]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/27 Word Embeddings.ipynb|27 Word Embeddings]] -->  | [[https://towardsdatascience.com/word-embedding-with-word2vec-and-fasttext-a209c1d3e12c|Word2Vec and FastText Word Embedding with Gensim]]  |  [[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 Tuesday, Oct. 20, 10:00 PM.   +| Week 9:\\ Oct 19 - Oct 23  | Natural language processing.   | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/18 Introduction to Natural Language Processing.ipynb|18 Introduction to Natural Language Processing]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/19 More NLP.ipynb|19 More NLP]] <!-- \\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/27 Word Embeddings.ipynb|27 Word Embeddings]] -->  | [[https://towardsdatascience.com/word-embedding-with-word2vec-and-fasttext-a209c1d3e12c|Word2Vec and FastText Word Embedding with Gensim]]  |  [[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 Tuesday, Oct. 20, 10:00 PM. Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]  
-| Week 10:\\ Oct 26 - Oct 30  | 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 10:\\ Oct 26 - Oct 30  | Introduction to Neural Networks  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/20 Introduction to Neural Networks.ipynb|20 Introduction to Neural Networks]]\\  [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/21 Pytorch Neural Networks.ipynb|21 Pytorch 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    [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A5.1 Min-Conflicts.ipynb|A5.1 Min-Conflicts]] due Friday Oct 30, 10:00 PM. Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]   |
  
  
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 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 11:\\ Nov 2 - Nov 6  | 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]] -->  |    | A5 due Monday Nov 2.    +| Week 11:\\ Nov 2 - Nov 6  | More Neural Networks  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/22 Classification with Pytorch Neural Networks.ipynb|22 Classification with Pytorch 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]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/22 Autoencoder Neural Networks.ipynb|22 Autoencoder Neural Networks]] -->  |    |     
-| Week 12:\\ Nov 9 - Nov 13  | Introduction to ClassificationBayes RuleGenerative versus DiscriminativeLinear Logistic Regression | <!-- [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/18 Introduction to Classification.ipynb|18 Introduction to Classification]] -->  |     |  +| Week 12:\\ Nov 9 - Nov 13  | Interpreting what a neural network has learned  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/23 Interpreting What a Neural Network Has Learned.ipynb|23 Interpreting What a Neural Network Has Learned]]   <!-- [[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/A6 Neural Networks.ipynb|A6 Neural Networks]] due <color red>Sunday Nov 15, 10:00 PM.</color>\\ Here are [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/goodones|good solutions from your classmates]]   
-| Week 13:\\ Nov 16 - Nov 20  | Classification with Neural NetworksReinforcement 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]]  -->  |    | A6 due Monday Nov 16  |+| Week 13:\\ Nov 16 - Nov 20  | Natural language processing with neural nets  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/24 NLP With Transformers.ipynb|24 NLP With Transformers]]  <!-- [[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]]  -->  |    |  |
 |  Nov 23 - Nov 27  |  Fall Recess!  | |  Nov 23 - Nov 27  |  Fall Recess!  |
  
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 ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^ ^  Week      ^  Topic      ^  Material  ^  Reading          ^  Assignments  ^
-| Week 14:\\ Nov 30 - Dec 4  | Reinforcement Learning with Neural Networks   <!-- [[http://www.cs.colostate.edu/~anderson/cs440/notebooks/15ijcnn.pdf|Slides for Faster Reinforcement Learning After Pretraining]] -->   [[http://www.cs.colostate.edu/~anderson/res/rl/pretrainijcnn15.pdf|Faster Reinforcement Learning After Pretraining Deep Networks to Predict State Dynamics]] by Anderson, Lee and Elliott  <!-- [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A6 Min-Conflicts.ipynb|A6 Min-Conflicts]] due WednesdayNov. 28, 10:00 PM.  -->  |  +| Week 14:\\ Nov 30 - Dec 4  | Clustering. Word embeddings.\\ Genetic algorithms.  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/25 Clustering of Word Embeddings.ipynb|25 Clustering of Word Embeddings]]\\ [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/26 Genetic Algorithm Search.ipynb|26 Genetic Algorithm Search]]   |  | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A7.1 NLP with Transformers and the T5 Model.ipynb|A7.1 NLP with Transformers and the T5 Model]] due SundayDec 6, 10:00 PM   |  
-| Week 15:\\ Dec 7 - Dec 11  | Recent AI Success  <!-- **Dec 3:**\\ Tom Cavey: //Image Classification and Object Detection of Things Around CSU//\\ Jason Stock: //Classification of Data from the Sloan Digital Sky Survey//\\ Marylou Nash: //Physical Routing on ICs or PCBs with A*//\\  **Dec 5:**\\ Jake Walker: //Legal, Ethical, and Security Concerns for Autonomous Driving Technologies//\\ Andy Dolan: //Using Machine Learning Methods to Classify BGP Messages//\\ Miles Wood: //Using Q-Learning to Learn to Play Chad, a Chess Variant//\\ Apoorv Pandey: //Using Q-Learning to Learn to Play 2x2 Dots and Boxes//\\ **Dec 7:**\\ Markus Dabell: //Classification of Handwritten Digits from the MNIST Dataset//\\ Sajeeb Roy Chowdhury: //Searching for Optimal Schreier Trees in the Field of Combinatorics//\\ Mike Hamilton: //The Amazon AWS DeepRacer Platform for Reinforcement Learning Experimentation//  -->  |   |  +| Week 15:\\ Dec 7 - Dec 11  | Brain-Computer Interfaces    |   |  
-| Final Exam Week:\\ Dec 14 - Dec 18  | No exam.    |  | | Final assignment due Dec 15th.   |+| Final Exam Week:\\ Dec 14 - Dec 18  | No exam.    |  | | [[http://nbviewer.ipython.org/url/www.cs.colostate.edu/~anderson/cs440/notebooks/A8 Report Template.ipynb|A8 Report Template]] due Tuesday, December 15th, 10:00 PM.   |
  
  
start.txt · Last modified: 2024/01/08 18:40 (external edit)