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Watching Neural Networks Learn [video]

2 pointsby allangrantover 1 year ago

1 comment

allangrantover 1 year ago
A video about neural networks, function approximation, machine learning, and mathematical building blocks. This is a submission for #SoME3<p>(0:00) Functions Describe the World<p>(3:15) Neural Architecture<p>(5:35) Higher Dimensions<p>(11:55) Taylor Series<p>(15:20) Fourier Series<p>(21:25) The Real World<p>(24:32) An Open Challenge<p>Links and Content:<p>• On Mathematical Maturity, Thomas Garrity: <a href="https:&#x2F;&#x2F;youtube.com&#x2F;watch?v=zHU1xH6Ogs4">https:&#x2F;&#x2F;youtube.com&#x2F;watch?v=zHU1xH6Ogs4</a><p>• Earth Rotation Loop: <a href="https:&#x2F;&#x2F;youtube.com&#x2F;watch?v=aiQdLP2mBJE">https:&#x2F;&#x2F;youtube.com&#x2F;watch?v=aiQdLP2mBJE</a><p>• Earth Rotation Loop Modeling Shell Surfaces: <a href="https:&#x2F;&#x2F;www.geogebra.org&#x2F;m&#x2F;xtv7zpn5" rel="nofollow noreferrer">https:&#x2F;&#x2F;www.geogebra.org&#x2F;m&#x2F;xtv7zpn5</a><p>• Fourier Features Paper: <a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2006.10739" rel="nofollow noreferrer">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2006.10739</a><p>• Code for mandelbrot&#x2F;image approximations: <a href="https:&#x2F;&#x2F;github.com&#x2F;MaxRobinsonTheGreat&#x2F;mandelbrotnn">https:&#x2F;&#x2F;github.com&#x2F;MaxRobinsonTheGreat&#x2F;mandelbrotnn</a><p>• Code for line&#x2F;surface approximations: <a href="https:&#x2F;&#x2F;github.com&#x2F;MaxRobinsonTheGreat&#x2F;ManimApproximations">https:&#x2F;&#x2F;github.com&#x2F;MaxRobinsonTheGreat&#x2F;ManimApproximations</a>