Automatic Differentiation

Also called autograd or back propagation (in the case of deep neural networks).
Here is the demo code: github.com/cg-tuwien/deep_lea...

[@ayushthada9544]

This is the best thing available on youtube about automatic differentiation.

[@sriramseshadri1998]

This is the clearest practical exposition to AD that I have found so far. Thanks!

[@heeiihee]

"this is my first video , bear with me" *proceeds to give the clearest explanation to AD in youtube*

[@reinholdpreiner4854]

Nicely presented overview, thanks!

[@mangaenfrancais934]

Thank u, the best explanation i found in KZbin

[@albertog2196]

Very clear explanation. Thanks

[@lllepricon7715]

Wow, cool stuff. Thank you!

[@jairjuliocc]

Thank you. I finally understand they topic

[@AJ-et3vf]

Awesome video! Thank you!

[@mkdaremo]

Excellent!

[@vtrandal]

Thank you! Very good!

[@sapito169]

sooooo coooool congratulation

[@tooljerk666]

May be my lack of mathematical understanding, but in the first example, 8 is the derivative and the 5, 3, and 1, 1, 1 are partial derivatives?

[@pleasetakemyadvice]

What's the purpose of the demo code ?