ML @ University of Virginia
Education
Empowering the next generation of ML practitioners through lectures, reading groups, and curated resources.
Lectures
Weekly lectures exploring cutting-edge ML concepts and practical applications.
ML in the cloud
4/22/2026
AI Agents
4/15/2026John Kim and Josh Yoo
Linear Regression
4/8/2026Utkarsh Goyal
YOLO
4/1/2026Anmol Thapa and Benjamin Hayworth
Vision Transformer
3/25/2026Logan Bradley and Ishan Ajwani
Alignment
3/18/2026Seth Lifland
Mechanistic Interpretability
3/11/2026Seth Lifland
Reinforcement Learning Part 2
2/25/2026Seth Lifland
Reinforcement Learning Part 1
2/18/2026Seth Lifland
Large Language Models
2/11/2026Shubhrangshu Debsarkar and Seth Lifland
Transformers Part 3
2/4/2026Seth Lifland
Transformers Part 2
1/28/2026Shubhrangshu Debsarkar and Seth Lifland
Transformers Part 1
1/21/2026Shubhrangshu Debsarkar
Review of Neural Networks
1/14/2026Raffi Khondaker
Diffusion Models
12/3/2025Raffi Khondaker
Generative Adverserial Networks
11/19/2025Raffi Khondaker
Autoencoders & Variational Autoencoders (VAEs)
11/5/2025Raffi Khondaker
Using CS Server
11/2/2025Raffi Khondaker
Optimization Techniques
10/22/2025Raffi Khondaker
Recurrent Neural Networks (RNNs)
10/15/2025Shubhrangshu Debsarkar
Convolutional Neural Networks (CNNs)
10/1/2025Raffi Khondaker
[Intro] Training Pipeline + Code
9/24/2025Raffi Khondaker
[Intro] Training a Neural Network
9/17/2025Raffi Khondaker
[Intro] Introduction to Deep Learning
9/10/2025Raffi Khondaker