All Machine Learning Terms Explained in 22 Minutes

[@divyanshpandey8355]

Hi, I subbed you 3 days ago, here to take the credit of being with you from start before you get to the top. Cheers!

[@josephthehansen]

Incredibly well made and informative, this channel is a goldmine. Would love to have a video covering more advanced concepts like activation functions, transformers, autoencoders, etc.

[@muhammaduuu]

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[@whiteduck5563]

Your channel is very informative. I'm actually learning ML by the steps you laid out in your other video.

[@Datalata]

This was super helpful. Should make it compulsory for all introductory ML courses. Sometimes a little hard to keep up, but that’s probably more to do with my more limited cognitive abilities!

[@Let010l01go]

Excellent knowledge!, Please keep on, this skill will to be expanded to other deeper as a baby try to grab as natural learning, guy!. GOOD E.P🎉

[@nero_Corleone]

Hey would it be possible to contact you for some Questions or even an Interview? Me and a fellow student are working on a study for a guide for AI implementation in the Maintenance field. We would really appreciate your input on some topics regarding the AI field. Best wishes from Germany!

[@AdiSetiawan-y7x]

Amazing!!!

[@ramshegokar]

Super duper

[@rotteclaw234]

16:00 not sure if cross validation is explained completely correctly, and if you google cross-validation you sometimes get different pictures about cross-validation. some explain cross validation where the test-set is one of the splits. and you do k iterations, having a different test set every time. any care to elaborate?

[@InfiniteCodes_]

The test set is the very final set. What you talk about is the validation set as explained in the video. You do cross validation not cross testing:) testing is after training is done

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[@InfiniteCodes_]

what a very specific image haha. Thank you!

[@williamdooresq]

Grumble, grumble ... Activation function ... grumble