Lectures

Lecture 1

• Topic: Linear Regression
• Notes / Slides
• Recording

Lecture 2

• Topic: Linear Algebra Review
• Notes / Slides
• Recording
• Additional Links:
  • Typed notes
  • Gill Strang Linear Algebra Lecture Notes

Lecture 3

• Topic: SVD and Regression
• Notes / Slides
• Recording
• Additional Links:
  • PRML Slides

Lecture 4

• Topic: Regularization in Regression
• Notes / Slides
• Recording

Lecture 5

• Topic: Matrix Factorization for Recommendation
• Notes / Slides
• Recording

Lecture 6

• Topic: Probability Theory Review
• Notes / Slides
• Recording

Lecture 7

• Topic: Introduction to Classification
• Notes / Slides
• Recording

Lecture 8

• Topic: Logistic Regression
• Notes / Slides
• Recording

Lecture 9

• Topic: Introduction to Deep Learning
• Notes / Slides
• Recording

Lecture 10

• Topic: Perceptron and SVM
• Notes / Slides
• Recording

Lecture 11

• Topic: SVMs and Duality
• Notes / Slides
• Recording

Lecture 12

• Topic: Hands on Machine Learning
• Notes / Slides
• Recording
• Additional Links:
  • Jupyter Notebook

Lecture 13

• Topic: Non Linear SVMs
• Notes / Slides
• Recording

Lecture 14

• Topic: Clustering
• Notes / Slides
• Recording

Lecture 15

• Topic: Class Projects Discussion
• Notes / Slides
• Recording To be released

Lecture 16

• Topic: Optimization Methods (Gradient Descent, SGD, Momentum, Adam)
• Notes / Slides
• Recording

Lecture 17

• Topic: Language Modeling Part 1
• Notes / Slides
• Recording

Lecture 18

• Topic: Language Modeling Part 2
• Notes / Slides
• Recording

Lecture 19

• Topic: Graph Clustering
• Notes / Slides
• Recording

Lecture 20

• Topic: LLM Prompting and Fine-tuning
• Notes / Slides
• Recording

Lecture 21

• Topic: Distributed Transformer Training
• Notes: To be released
• Recording

Lecture 22

• Topic: Diffusion Models
• Notes / Slides
• Recording

Lecture 23

• Topic: Intro to RL & Application to LLMs
• Notes / Slides
• Recording