Schedule

This tentative schedule will be updated during the semester.

August

Week	Topic	Material	Reading	Assignments
Week 1: Aug 24, 26	Overview of course. Review of neural networks training and use.	01 Introduction to CS545 02 Searching for Good Weights in a Linear Model		Ungraded Quiz 1 due Friday, August 27, 10:00 PM
Week 2: Aug 31, Sept 2	Regression with neural networks.	03 Fitting Simple Models Using Gradient Descent in the Squared Error 04 Introduction to Neural Networks

Week	Topic	Material	Reading	Assignments
Week 3: Sept 7, 9	A1 questions. Optimizers. Neural Network class.	05 Optimizers		A1 Three-Layer Neural Network due Wednesday, Sept 8th, at 10:00 PM
Week 4: Sept 14, 16	A2. Autoencoders. Classification.	06 Autoencoders 07 Introduction to Classification
Week 5: Sept 21, 23	A2 questions. Classification.	08 Classification with Linear Logistic Regression 09 Classification with Nonlinear Logistic Regression Using Neural Networks		A2 NeuralNetwork Class due Tuesday, Sept. 21, at 10:00 PM . Examples of good solutions are available here.
Week 6: Sept 28, 30	Lectures and Chuck's office hours canceled this week. Prerecorded lectures available in Echo360 in Canvas on Jax and Streamlit packages.	10 JAX neuralnetworks_app.tar	JAX Ecosystem Streamlit

Week	Topic	Material	Reading	Assignments
Week 7: Oct 5, 7	Convolutional neural networks.	11 Convolutional Neural Networks CNN Backpropagation Notes	The Great AI Reckoning	A3 Neural Network Classifier due Friday, Oct 8, at 10:00 PM. Examples of good solutions are available here.
Week 8: Oct 12, 14	Pytorch. Convolutional neural nets	12 Introduction to Pytorch 13 Convolutional Neural Networks in Pytorch 14 Convolutional Neural Networks in Numpy
Week 9: Oct 19, 21	Reinforcement Learning	15 Introduction to Reinforcement Learning 16 Reinforcement Learning with Neural Network as Q Function
Week 10: Oct 26, 28	Reinforcement Learning Oct 28 in-person lecture and office hours are canceled. Please watch the recorded lecture available in Canvas Echo360 available by Oct 29.	17 Reinforcement Learning for Two Player Games 18 Reinforcement Learning to Control a Marble 19 Reinforcement Learning Modular Framework		A4.2 Convolutional Neural Networks due Monday, Oct 25, at 10:00 PM.

Week	Topic	Material	Reading	Assignments
Week 11: Nov 2, 4	Transfer learning in Reinforcement Learning. Brain-Computer Interfaces	Slide presentations	Faster Reinforcement Learning After Pretraining Deep Networks to Predict State Dynamics, Increased Reinforcement Learning Performance through Transfer of Representation Learned by State Prediction Model	Project Proposal and Report Example due Friday, Nov. 5, at 10:00 PM.
Week 12: Nov 9, 11	BCI. Recurrent Neural Networks.	20 Recurrent Networks in Numpy 21 Recurrent Networks in Pytorch 22 Classifying EEG Using Recurrent Neural Networks
Week 13: Nov 16, 18	K-means clustering. K-nearest-neighbor classification. Support Vector Machines.	23 K-Means Clustering, K-Nearest-Neighbor Classification 24 Support Vector Machines		A5.1 Reinforcement Learning on Marble with Variable Goal due Monday, Nov 15th at 10:00 PM. Examples of good solutions are available here.
Nov 23, 25	Fall Recess !!
Week 14: Nov 30, Dec 2	Introduction to Transformers	25 Introduction to Transformers

Week	Topic	Material	Reading	Assignments
Week 15: Dec 7, 9	Transformers: Self-Attention Replaced by Fourier Transform. Cascade Ensemble Network	26 FNet--Replace Self-Attention with Fourier Transform 27 Cascade Ensemble Network
Dec 13-17	Final Exam Week	No Exams in this course		Final project reports are due Tuesday, Dec. 14th, 10:00 PM.