Date Lecture Suggested Readings Logistics
09/27 Lecture #1:
Overview
[ slides ]

10/02 Lecture #2:
Overview
[ slides see above ]

10/04 Lecture #3:
Overview
[ slides see above ]

10/07 Lecture #4:
Large Language Models
[ slides ]

10/09 Lecture #5:
Self-Supervised Learning
[ slides ]

10/11 Lecture #6:
Self-Supervised Learning
[ slides ]

10/14 Lecture #7:
Enhancing LLMs
[ slides ]

10/16 Lecture #8:
Enhancing LLMs / (Un)supervised Learning
[ slides ]

10/18 Lecture #9:
Unsupervised Learning
[ slides (pptx) ]

10/21 Lecture #10:
Unsupervised Learning (EM)
[ slides (pptx) ]

10/23 Lecture #11:
Guest Lecture
[ Slides to be added ]

10/25 Lecture #12:
Guest Lecture
[ Slides to be added ]

10/28 Lecture #13:
Unsupervised Learning (EM)
[ slides (pptx) ]

10/30 Lecture #14:
Unsupervised Learning (EM)
[ slides ]

11/01 Lecture #15:
Unsupervised Learning (VI)
[ slides ]

11/04 Lecture #16:
Unsupervised Learning (VI)
[ slides ]

11/06 Lecture #17:
Unsupervised Learning (VI)
[ slides ]

11/08 Lecture #18:
Unsupervised Learning (VAEs)
[ slides ]

11/11 No Lecture:
Veterans Day

11/13 Lecture #19:
Unsupervised Learning, Reinforcement Learning
[ slides ]

11/15 Lecture #20:
Reinforcement Learning
[ slides ]

11/18 Lecture #21:
Reinforcement Learning
[ slides ]

11/20 Lecture #22:
Reinforcement Learning
[ slides ]

11/22 Lecture #23:
Reinforcement Learning
[ slides ]

11/25 Lecture #24:
RLHF
[ slides ]

11/27 Lecture #25:
Standard Model of ML
[ slides ]

12/29 No Lecture:
Thanksgiving Holiday

12/02 Lecture #:
Final project presentation

12/04 Lecture #:
Final project presentation

12/06 Lecture #:
Final project presentation

Final Week

Project final report due