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start [2019/02/28 09:11]
anderson [February]
start [2019/06/03 13:46] (current)
anderson [May]
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 ===== Announcements ===== ===== Announcements =====
  
-This is tentative schedule.  ​Changes will be made as the semester progresses.+Thanks, everyone, for fun semester.  ​I very much enjoyed reading your final reports ​Follow [[http://​www.cs.colostate.edu/​~anderson/​cs445/​projects|this link]] to read the reports
  
 ===== January ===== ===== January =====
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 | Week 4:\\ Feb 11 - Feb 15   | Introduction to nonlinear regression with neural networks. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​08 Stochastic Gradient Descent with Parameterized Activation Function.ipynb|08 Stochastic Gradient Descent with Parameterized Activation Function]] ​ | [[http://​www.deeplearningbook.org/​|Deep Learning]], Chapter 6 (skip 6.2)  |  [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A1 Stochastic Gradient Descent for Simple Models.ipynb|A1 Stochastic Gradient Descent for Simple Models]] due Tuesday, February 12, 10:00 PM.\\ [[http://​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​good-ones/​|Examples of good solutions]] ​  | | Week 4:\\ Feb 11 - Feb 15   | Introduction to nonlinear regression with neural networks. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​08 Stochastic Gradient Descent with Parameterized Activation Function.ipynb|08 Stochastic Gradient Descent with Parameterized Activation Function]] ​ | [[http://​www.deeplearningbook.org/​|Deep Learning]], Chapter 6 (skip 6.2)  |  [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A1 Stochastic Gradient Descent for Simple Models.ipynb|A1 Stochastic Gradient Descent for Simple Models]] due Tuesday, February 12, 10:00 PM.\\ [[http://​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​good-ones/​|Examples of good solutions]] ​  |
 | Week 5:\\ Feb 18 - Feb 22  | More neural networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​09 Scaled Conjugate Gradient for Training Neural Networks.ipynb|09 Scaled Conjugate Gradient for Training Neural Networks]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​10 More Nonlinear Regression with Neural Networks.ipynb|10 More Nonlinear Regression with Neural Networks]] ​ |   ​| ​   | Week 5:\\ Feb 18 - Feb 22  | More neural networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​09 Scaled Conjugate Gradient for Training Neural Networks.ipynb|09 Scaled Conjugate Gradient for Training Neural Networks]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​10 More Nonlinear Regression with Neural Networks.ipynb|10 More Nonlinear Regression with Neural Networks]] ​ |   ​| ​  
-| Week 6:\\ Feb 25 - Mar 1  | Autoencoders. Activation functions. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​11 Autoencoder Neural Networks.ipynb|11 Autoencoder Neural Networks]] ​ | [[https://​arxiv.org/​pdf/​1710.05941.pdf|Searching for Activation Functions]],​ by Ramachandran,​ Zoph, and Le\\ [[http://​aclweb.org/​anthology/​D18-1472|Is it time to swish?]], by Eger, Youssef, and Gurevych ​  ​| ​ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A2 Adam vs SGD.ipynb|A2 Adam vs SGD]] due Tuesday February 26, 10:00 PM.  |+| Week 6:\\ Feb 25 - Mar 1  | Autoencoders. Activation functions. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​11 Autoencoder Neural Networks.ipynb|11 Autoencoder Neural Networks]] ​ | [[https://​arxiv.org/​pdf/​1710.05941.pdf|Searching for Activation Functions]],​ by Ramachandran,​ Zoph, and Le\\ [[http://​aclweb.org/​anthology/​D18-1472|Is it Time to SwishComparing Deep Learning Activation Functions Across NLP tasks]], by Eger, Youssef, and Gurevych ​  ​| ​ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A2 Adam vs SGD.ipynb|A2 Adam vs SGD]] due Tuesday February 26, 10:00 PM.  |
  
 ===== March ===== ===== March =====
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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 7:\\ Mar 4 - Mar 8  | Classification. LDA and QDA. K-Nearest Neighbors. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​12 Introduction to Classification.ipynb|12 Introduction to Classification]] \\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​13 Gaussian Distributions.ipynb|13 Gaussian Distributions]] ​  ​| ​ | | +| Week 7:\\ Mar 4 - Mar 8  | Classification. LDA and QDA. K-Nearest Neighbors. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​12 Introduction to Classification.ipynb|12 Introduction to Classification]] \\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​13 Gaussian Distributions.ipynb|13 Gaussian Distributions]] ​  ​| ​[[https://​towardsdatascience.com/​jupyter-lab-evolution-of-the-jupyter-notebook-5297cacde6b|Jupyter Lab: Evolution of the Jupyter Notebook]] by Parul Pandey ​ | | 
-| Week 8:\\ Mar 11 - Mar 15   | Classification with Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​14 Classification with Linear Logistic Regression.ipynb|14 Classification with Linear Logistic Regression]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​15 Classification with Nonlinear Logistic Regression Using Neural Networks.ipynb|15 Classification with Nonlinear Logistic Regression Using Neural Networks]] ​\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​16 Introduction to Pytorch.ipynb|16 Introduction to Pytorch]]  |+| Week 8:\\ Mar 11 - Mar 15   | Classification with Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​14 Classification with Linear Logistic Regression.ipynb|14 Classification with Linear Logistic Regression]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​15 Classification with Nonlinear Logistic Regression Using Neural Networks.ipynb|15 Classification with Nonlinear Logistic Regression Using Neural Networks]] ​ ​| ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A3 Neural Network Regression and Activation Functions.ipynb|A3 Neural Network Regression and Activation Functions]] due Friday March 15, 10:00 PM.  |
 |  Mar 18 - Mar 22  |  Spring Break  | |  Mar 18 - Mar 22  |  Spring Break  |
-| Week 9:\\ Mar 25 - Mar 29 | Analysis of Trained Networks. Bottleneck Networks. Classifying Hand-Drawn Digits.  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​17 Analysis of Neural Network Classifiers and Bottleneck Networks.ipynb|17 Analysis of Neural Network Classifiers and Bottleneck Networks]] ​ \\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​18 Dealing with Time Series by Time-Embedding.ipynb|18 Dealing with Time Series by Time-Embedding]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​19 Recurrent Neural Networks.ipynb|19 Recurrent Neural Networks]]  | | |+| Week 9:\\ Mar 25 - Mar 29 | Pytorch.  | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​16 Introduction to Pytorch.ipynb|16 Introduction to Pytorch]]  | | |
  
 ===== April ===== ===== April =====
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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 10:\\ Apr 1 - Apr 5  | Convolutional Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​20 Classifying Hand-drawn Digits.ipynb|20 Classifying Hand-drawn Digits]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​21 Convolutional Neural Networks.ipynb|21 Convolutional Neural Networks]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​22 Introduction to Reinforcement Learning.ipynb|22 Introduction to Reinforcement Learning]]  | [[http://incompleteideas.net/book/the-book.html|Reinforcement LearningAn Introduction]], by Sutton and Barto, 2nd ed.   |  | +| Week 10:\\ Apr 1 - Apr 5  | Pytorch. ​Convolutional Neural Networks ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​17 Pytorch autograd, nn.Module.ipynb|17 Pytorch autograd, nn.Module]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​18 Convolutional Neural Networks.ipynb|18 Convolutional Neural Networks]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​19 Convolutional Neural Networks in Pytorch.ipynb|19 Convolutional Neural Networks in Pytorch]]  | [[https://towardsdatascience.com/getting-started-with-pytorch-part-1-understanding-how-automatic-differentiation-works-5008282073ec|Pytorch Automatic Differentiation]]\\ [[https://​www.youtube.com/​watch?​v=MswxJw-8PvE|PyTorch Autograd Explained - In-depth Tutorial]], by Elliott Waite   |  | 
-| Week 11:\\ Apr 8 - Apr 12   | Reinforcement Learning. Games using Tabular Q functions. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​23 Reinforcement Learning with Neural Network as Q Function.ipynb|23 Reinforcement Learning with Neural Network as Q Function]] ​ |  | [[https://drive.google.com/open?​id=1KHAxeIwL3ait2ZUbILdbJjCLW47JwxKpdjsAr5kkkZk|Project proposal]] due at 10 pm Friday evening. You are welcome to start with a copy of the linked Google Doc.   | +| Week 11:\\ Apr 8 - Apr 12   | Reinforcement Learning. Games using Tabular Q functions. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​22 Introduction to Reinforcement Learning.ipynb|22 Introduction to Reinforcement Learning]]\\ ​[[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​23 Reinforcement Learning with Neural Network as Q Function.ipynb|23 Reinforcement Learning with Neural Network as Q Function]] ​ | [[http://​incompleteideas.net/​book/​the-book.html|Reinforcement Learning: An Introduction]],​ by Sutton and Barto, 2nd ed.  | [[http://nbviewer.ipython.org/url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​Project Proposal.ipynb|Project proposal]] due at 10 pm Friday evening. ​  | 
-| Week 12:\\ Apr 15 - Apr 19  | Reinforcement Learning using Neural Networks as Q functions. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​24 Reinforcement Learning to Control a Marble.ipynb|24 Reinforcement Learning to Control a Marble]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​25 Reinforcement Learning for Two Player Games.ipynb|25 Reinforcement Learning for Two Player Games]] ​  | +| Week 12:\\ Apr 15 - Apr 19  | Reinforcement Learning using Neural Networks as Q functions. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​24 Reinforcement Learning to Control a Marble.ipynb|24 Reinforcement Learning to Control a Marble]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​25 Reinforcement Learning for Two Player Games.ipynb|25 Reinforcement Learning for Two Player Games]] ​  |   | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​A4 Classifying Hand-Drawn Digits.ipynb |A4 Classifying Hand-Drawn Digits]] due Wednesday, April 17  ​
-| Week 13:\\ Apr 22 - Apr 26  | Unsupervised Learning. Dimensionality Reduction. ​ Clustering. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​26 ​Linear Dimensionality Reduction.ipynb|26 ​Linear Dimensionality Reduction]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​27 ​Examples of Linear Dimensionality Reduction.ipynb|27 ​Examples of Linear Dimensionality Reduction]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​28 K-Means Clustering.ipynb|28 K-Means Clustering]] ​ |+| Week 13:\\ Apr 22 - Apr 26  | Unsupervised Learning. Dimensionality Reduction. ​ Clustering. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​26 ​Genetic Algorithm Search.ipynb|26 ​Genetic Algorithm Search]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​27 Linear Dimensionality Reduction.ipynb|27 Linear Dimensionality Reduction]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​28 K-Means Clustering.ipynb|28 K-Means Clustering]] ​ |
 | Week 14:\\ Apr 29 - May 3  | Hierarchical clustering. K Nearest Neighbors Classification. Support Vector Machines. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​29 Hierarchical Clustering.ipynb|29 Hierarchical Clustering]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​30 Nonparametric Classification with K Nearest Neighbors.ipynb|30 Nonparametric Classification with K Nearest Neighbors]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​31 Support Vector Machines.ipynb|31 Support Vector Machines]] ​ |  |  } | Week 14:\\ Apr 29 - May 3  | Hierarchical clustering. K Nearest Neighbors Classification. Support Vector Machines. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​29 Hierarchical Clustering.ipynb|29 Hierarchical Clustering]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​30 Nonparametric Classification with K Nearest Neighbors.ipynb|30 Nonparametric Classification with K Nearest Neighbors]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​31 Support Vector Machines.ipynb|31 Support Vector Machines]] ​ |  |  }
  
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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 6 - May 10  | Ensembles. ​ Other topics. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​32 Ensembles of Convolutional Neural Networks.ipynb|32 Ensembles of Convolutional Neural Networks]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​33 Machine Learning for Brain-Computer Interfaces.ipynb|33 Machine Learning for Brain-Computer Interfaces]]\\ ​ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​34 Modeling Global Climate Change.ipynb|34 Modeling Global Climate Change]] ​ |  | Final Project Report due Wednesday, May 8, 10:00 PM. Here is a [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​Project Report Example.ipynb|Project Report Example]]  | +| Week 15:\\ May 6 - May 10  | Ensembles. ​ Other topics. ​ | [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​32 Ensembles of Convolutional Neural Networks.ipynb|32 Ensembles of Convolutional Neural Networks]]\\ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​33 Machine Learning for Brain-Computer Interfaces.ipynb|33 Machine Learning for Brain-Computer Interfaces]]\\ ​ [[http://​nbviewer.ipython.org/​url/​www.cs.colostate.edu/​~anderson/​cs445/​notebooks/​34 Modeling Global Climate Change.ipynb|34 Modeling Global Climate Change]] ​ ​| ​ |  | 
-| May 13 - May 16  |  Final Exams  |  |  |  |+| May 13 - May 16  |  Final Exams  |  ​| ​ | Final Project Report due Tuesday, May 14, 10:00 PM. Here are is a [[http://​www.cs.colostate.edu/​~anderson/​cs445/​projects|links to most of the project reports]]  |
  
  
  
start.1551370309.txt.gz · Last modified: 2019/02/28 09:11 by anderson