User Tools

Site Tools


schedule




The following schedule is tentative and is being updated.

All students may attend the lecture remotely using this zoom link.

August

Week Topic Lecture Notes Reading Assignments
Week 1:
Aug 20, 22
Course overview.
Machine Learning and AI: History and Present Boom
Jupyter notebooks.
01 Introduction to CS545
01a Simple Animations
02 Searching for Good Weights in a Linear Model
JupyterLab Introduction, watch the video then play with jupyter lab.
What is Data Analysis? How to Visualize Data with Python, Numpy, Pandas, Matplotlib & Seaborn Tutorial, by Aakash NS
Not graded: Please fill out this anonymous survey before Thursday class.
Week 2:
Aug 27, 29
Optimization algorithms. Simple linear and nonlinear models. Confidence intervals. 02 Searching for Good Weights in a Linear Model
02a Input Importance and Generative AI---Friend or Foe
03 Fitting Simple Models Using Gradient Descent in the Squared Error
04 Training Multiple Models to Obtain Confidence Intervals

September

Week Topic Lecture Notes Reading Assignments
Week 3:
Sept 3, 5
Introduction to neural networks. 05 Introduction to Neural Networks 3Blue1Brown Introduction to Neural Networks in the first five chapters provides a fun video tutorial including error backpropagation.
Week 4:
Sept 10, 12
Design of NeuralNetwork class. Optimizers. Overview of A2. Memory organization for neural network parameters. Optimizers tailored for neural networks. 06 Python Classes
07 Optimizers Simple
08 Collecting All Weights into One-Dimensional Vector for Use in Optimizers
08a Optimizers
Weight Initialization for Deep Learning Neural Networks, by Jason Brownlee A1 due Monday, September 9th, 10:00 PM.
Week 5:
Sept 17, 19
Chuck's office hours cancelled today.
Introduction to Classification. 09 Introduction to Classification A2 NeuralNetwork Class due Thursday, September 19, 10:00 PM. Notebook and A2grader updated Sept. 12, 5:30 pm.
Week 6:
Sept 24, 26
Early stopping (new version of optimizers). A3. Introduction to classification.

October

Week Topic Lecture Notes Reading Assignments
Week 7:
Oct 1, 3
Classification with QDA, LDA, and linear logistic regression.
Week 8:
Oct 8, 10
Classification with Nonlinear Logistic Regression. Introduction to Reinforcement Learning.
Week 9:
Oct 15, 17
Reinforcement learning with Q Function as Neural Network. Learning to play games. Last Week in AI
Geoffrey Hinton: AI Dangers, on 60 Minutes
Week 10:
Oct 22, 24
Modular framework for reinforcement learning. Convolutional Neural Networks.
Week 11:
Oct 29, 31
Pytorch.
Jax.
Ray.
President Biden's Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence

November

Week Topic Lecture Notes Reading Assignments
Week 12:
Nov 5, 7
Convolutional Neural Networks.
Week 13:
Nov 12, 14
Ensembles. Mixture of Experts.
Week 14:
Nov 19, 21
Clustering. K-Nearest Neighbors. Web Apps with Streamlit. ChatGPT generates fake data set to support scientific hypothesis
Fall Break:
Nov 25-29
No classes.

December

Week Topic Lecture Notes Reading Assignments
Week 15:
Dec 3, 5
Word embeddings. Transformers.
Dec 10-12 Final Exam Week No Exams in this course
schedule.txt · Last modified: 2024/09/19 10:43 by 127.0.0.1