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AI

Neural networks, transformers and language models, from first lecture to research talk.

49 entries, about 42 hours of single videos. Bloom scroll this shelf

49 entries
33 min Diffusion Models | Paper Explanation | Math ExplainedOutlier

Hi, thank you for your video. I had a hard time figuring out the equations for q's closed form, so I though I might share it here: At 13:11, you go from q(x_t, x_{t-1}) = sqrt(a_t) x_{t-1} + sqrt(1 - a_t) epsilon to q(x_t, x_{t-2}) = sqrt(a_t a_{t-1}) x_{t-2} + sqrt(1 - a_t a_{t-1}) epsilon If you substitute x_{

Mentioned in r/MachineLearning

Questions about AI videos

Where should I start with AI videos?

Good first picks here, chosen by the list’s editor because they build ideas up from the basics, are More Than Image Generators: A Science of Problem-Solving using Probability | Diffusion Models (52 min), The Breakthrough Behind Modern AI Image Generators | Diffusion Models Part 1 (24 min) and Gradient descent, how neural networks learn | Deep Learning Chapter 2 (21 min).

Are there short AI videos?

Yes. 5 run under 15 minutes, including Gradient Descent in 3 minutes (3 min) and Backpropagation calculus | Deep Learning Chapter 4 (10 min).

Are there full AI courses or lecture series?

19 entries are full course, lecture or playlist, such as Machine Learning — sentdex and Neural Networks for Machine Learning — Geoffrey Hinton.

Where on Reddit were these AI videos shared?

Most came up in r/MachineLearning (17), r/learnprogramming (9) and r/agi (5). A mention can be a recommendation, a question or an argument, and each video’s page says which it was.

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