Lipschitz Functions: Intro and Simple Explanation for Usefulness in Machine Learning

[@meghbhalerao5208]

Great intuitive explanation! Thank you!

[@DrMcCrady]

Glad it was helpful!

[@inerammeloo7915]

Thank you for making this! It was really well explained and helped a lot for me to grasp the concept

[@DrMcCrady]

Glad it was helpful!

[@hazema.6150]

Very nice breakdown, thank you so much for it.

[@DrMcCrady]

Glad it was helpful!

[@CodeEmporium]

Loved this

[@DrMcCrady]

Thank you! And you make great ML content, too!

[@karthikeyakethamakka]

I would say lipschitz is mostly used as a regularization technique for a machine learning problem.

[@SinghTheMaster]

You got a new subscriber ❤

[@tnuts92]

Thanks for the explanation of its interest for machine learning algorithms !! Thats all I'd like to understand about any math concept ! Cheers 🙏🙏

[@DrMcCrady]

Glad it was helpful, give math a chance though :)

[@soroushmehraban]

Awesome explanation. Keep going!

[@DrMcCrady]

Thanks for your kindness!

[@Mulkek]

Thanks, and it's so easy & simple!

[@QmiStudying]

do you have any idea on how to prove lotka-volterra equations is locally lipschitz

[@DrMcCrady]

In two dimensions, the two expressions for the changes in population are products of linear functions. Linear functions are Lipschitz. Use that to show the product is locally Lipschitz.

[@sukritkapil9816]

Thanks for the clear explanation!!

[@DrMcCrady]

Glad it was helpful!

[@victorezekiel5374]

Great video! Please what do you mean by between -K and K. Is the slope of the secant supposed to be K?

[@DrMcCrady]

The slope of the secant line would be between -K and K. So the difference between any two outputs is at most K times the difference between the corresponding inputs.

[@sam_joshua_s]

its the best video explaination

[@DrMcCrady]

Thank you!

[@hamzamohiuddin973]

Thank you, very easy to follow.

[@DrMcCrady]

Glad it was helpful!

[@harperbye]

Thank you, this was really helpful.

[@DrMcCrady]

Glad it was helpful!

[@jasonrichards5192]

Great Explanation!

[@DrMcCrady]

Thank you!

[@anirudhthatipelli8765]

Thanks a lot, this was very clear!

[@DrMcCrady]

Glad it was helpful!

[@Niki99fun]

This really helped me! Thank you

[@DrMcCrady]

Glad to hear it!

[@tuongnguyen9391]

Damn it this is so good !!!!!, May I ask what playlist this video belong to

[@DrMcCrady]

Thank you! I think it belongs to this one Real Analysis/Advanced Calculus
ua-cam.com/play/PLrvK1zCpb85AtQZjin-IJLRK4uOMX0Hji.html

[@tuongnguyen9391]

@@DrMcCrady not really the one in that playlist is only ""Lipschitz Functions"

[@toniguana]

gracias

[@DrMcCrady]

Glad it was helpful!

[@troisiemeoeil3651]

Thank you for the clear insight. I've been struggling with the underpinnings of statistical learning theory and videos such as yours are godsends.