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This tentative schedule will be updated during the semester.


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
JAX Ecosystem


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.
21fa-schedule.txt · Last modified: 2022/06/09 11:48 by