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A 27-minute video by Yannic Kilcher about transformers, attention and research papers, on the AI shelf. A commenter in r/MachineLearning recommended it.
Yannic Kilcher, Video, 27 min, 2017, on the AI shelf
Yannic Kilcher walks through the original Attention Is All You Need paper.
26 min
Building Your Own Language ModelVahid KazemiRecommended in r/MachineLearning
1 h 56 min
Let's build GPT: from scratch, in code, spelled out.Andrej KarpathyRecommended in r/learnmachinelearning
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
6 h 52 min
TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners TutorialfreeCodeCamp.orgMentioned in r/learnprogramming