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**This is an old revision of the document!**

The following schedule is **tentative and is being updated**.

Please send your suggestions regarding lecture topics to Chuck using this Google Docs form. Questions regarding assignments should be entered in Canvas discussions.

## August

Week | Topic | Material | Reading | Assignments |
---|---|---|---|---|

Week 1: Aug 23, 25 | Overview of course. Review of neural networks training and use. | 01 Introduction to CS545 02 Searching for Good Weights in a Linear Model | JupyterLab Introduction, watch the video then play with jupyter lab. | Quiz 1 due Friday, August 26, 10:00 PM |

Week 2: Aug 30, Sept 1 | Regression with neural networks. | 03 Fitting Simple Models Using Gradient Descent in the Squared Error 04 Introduction to Neural Networks |

## September

Week | Topic | Material | Reading | Assignments |
---|---|---|---|---|

Week 3: Sept 6, 8 | A1 questions. Optimizers. Neural Network class. | 05 Optimizers | ||

Week 4: Sept 13, 15 | A2. Autoencoders. Classification. | 06 Autoencoders 07 Introduction to Classification | ||

Week 5: Sept 20, 22 | Classification. | 08 Classification with Linear Logistic Regression 09 Classification with Nonlinear Logistic Regression Using Neural Networks | ||

Week 6: Sept 27, 29 | 10 JAX neuralnetworks_app.tar | JAX Ecosystem Streamlit |

## October

Week | Topic | Material | Reading | Assignments |
---|---|---|---|---|

Week 7: Oct 4, 6 | Convolutional neural networks. | 11 Convolutional Neural Networks CNN Backpropagation Notes | ||

Week 8: Oct 11, 13 | Pytorch. Convolutional neural nets | 12 Introduction to Pytorch 13 Convolutional Neural Networks in Pytorch 14 Convolutional Neural Networks in Numpy | ||

Week 9: Oct 18, 20 | Reinforcement Learning | 15 Introduction to Reinforcement Learning 16 Reinforcement Learning with Neural Network as Q Function | ||

Week 10: Oct 25, 27 | Reinforcement Learning | 17 Reinforcement Learning for Two Player Games 18 Reinforcement Learning to Control a Marble 19 Reinforcement Learning Modular Framework |

## November

Week | Topic | Material | Reading | Assignments |
---|---|---|---|---|

Week 11: Nov 1, 3 | Transfer learning in Reinforcement Learning. Brain-Computer Interfaces | Slide presentations | ||

Week 12: Nov 8, 10 | BCI. Recurrent Neural Networks. | 20 Recurrent Networks in Numpy 21 Recurrent Networks in Pytorch 22 Classifying EEG Using Recurrent Neural Networks | ||

Week 13: Nov 15, 17 | K-means clustering. K-nearest-neighbor classification. Support Vector Machines. | 23 K-Means Clustering, K-Nearest-Neighbor Classification 24 Support Vector Machines | ||

Week 14: Nov 29, Dec 1 | Introduction to Transformers | 25 Introduction to Transformers |

## December

Week | Topic | Material | Reading | Assignments |
---|---|---|---|---|

Week 15: Dec 6, 8 | Transformers: Self-Attention Replaced by Fourier Transform. Cascade Ensemble Network | 26 FNet--Replace Self-Attention with Fourier Transform 27 Cascade Ensemble Network | ||

Dec 12-16 | Final Exam Week | No Exams in this course |

start.1661187080.txt.gz · Last modified: 2022/08/22 10:51 by anderson