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A 26-minute video by Vahid Kazemi about language modeling, transformers and self-attention, on the AI shelf. A commenter in r/MachineLearning recommended it.
Vahid Kazemi, Video, 26 min, 2025, on the AI shelf
An introduction to building a language model with explanations of encoding, self-attention and transformers.
27 min
Attention Is All You NeedYannic KilcherRecommended in r/MachineLearning
1 h 56 min
Let's build GPT: from scratch, in code, spelled out.Andrej KarpathyRecommended in r/learnmachinelearning
8 min
Large Language Models explained briefly3Blue1BrownPosted to r/LocalLLaMA
1 h 15 min
Lecture 14 – Contextual Vectors | Stanford CS224U: Natural Language Understanding | Spring 2019Stanford OnlineRecommended in r/MachineLearning
54 min
Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 14 – Transformers and Self-AttentionStanford OnlineRecommended in r/MachineLearning
36 min
Fastformer: Additive Attention Can Be All You Need (Machine Learning Research Paper Explained)Yannic KilcherPosted to r/MachineLearning: [D] Paper Explained - Fastformer: Additive Attention Can Be All You Need (Full Video Analysis)
52 min
More Than Image Generators: A Science of Problem-Solving using Probability | Diffusion ModelsDepth FirstMentioned in r/StableDiffusion
24 min
The Breakthrough Behind Modern AI Image Generators | Diffusion Models Part 1Depth FirstPosted to r/StableDiffusion: The best tutorial on Diffusion I have seen so far