The uploader has turned off playing this outside YouTube.
A 54-minute lecture by Stanford Online about transformers, self-attention and natural language processing, on the AI shelf. A commenter in r/MachineLearning recommended it.
Stanford Online, Lecture, 54 min, 2019, on the AI shelf
A Stanford CS224N guest lecture on transformers and self-attention.
27 min
Attention Is All You NeedYannic KilcherRecommended in r/MachineLearning
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
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
