EfficientML.ai Lecture 12 - Transformer and LLM (Part I) (MIT 6.5940, Fall 2023)
EfficientML.ai Lecture 12 - Transformer and LLM (Part I) (MIT 6.5940, Fall 2023) Instructor: Prof. Song Han Slides: https://efficientml.ai
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EfficientML.ai Lecture 12 - Transformer and LLM (Part I) (MIT 6.5940, Fall 2023, Zoom)
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EfficientML.ai Lecture 9 - Knowledge Distillation (MIT 6.5940, Fall 2023)
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MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention
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LLM Agents MOOC | UC Berkeley CS294-196 Fall 2024 | LLM Reasoning by Denny Zhou
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How GPT, Claude, and Gemini are actually trained and served – Reiner Pope
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EfficientML.ai Lecture 14 - Vision Transformer (MIT 6.5940, Fall 2023)
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Visualizing transformers and attention | Talk for TNG Big Tech Day '24
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How a High School Student Overturned a Famous Conjecture
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MIT 6.S184: Flow Matching and Diffusion Models - Lecture 02: Flow Matching (2026)
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Stanford CS229 I Machine Learning I Building Large Language Models (LLMs)
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Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 8 - LLM Evaluation
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EfficientML.ai Lecture 20: Efficient Fine-tuning and Prompt Engineering (MIT 6.5940, Fall 2023)
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CS480/680 Lecture 19: Attention and Transformer Networks
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Stanford CME295 Transformers & LLMs | Autumn 2025 | Lecture 1 - Transformer
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EfficientML.ai Lecture 16 - Diffusion Model (MIT 6.5940, Fall 2023)
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Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker
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EfficientML.ai Lecture 19 - Distributed Training Part 1 (MIT 6.5940, Fall 2024)
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Stanford CS25: V2 I Introduction to Transformers w/ Andrej Karpathy
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LLM inference optimization: Architecture, KV cache and Flash attention
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