Course Notes
The notes written by students and edited by instructors
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Lecture 25
Alignment, explainability, and open research directions in modern machine learning, with a focus on large language models and system-level reliability.
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Lecture 24
Prompts and In-Context Learning
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Lecture 23
Supervised Fine-tuning of LLMs
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Lecture 22
Unsupervised Training of LLMs
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Lecture 21: GPT Architectures
From RNNs to Transformers to GPT - Understanding the evolution of modern language models
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Lecture 20
Attention and Transformers
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Lecture 19
Sequence Learning with RNNs
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Lecture 17
Generative Adversarial Networks (GANs)
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Lecture 16
Autoencoders and Variational Autoencoders (VAEs)
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Lecture 15
A Linear Intro to Generative Models
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