Quick explanation: One-hot encoding

What is one-hot encoding?
It is a way to feed categorical data to Machine Learning models.
Why do we use one-hot encoding?
Because Machine Learning models cannot handle categorical data in its raw form.
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[@tarek_maza]

Short, sweet, and straight to the point! Great job

[@Harirtaylorversion]

what a time to be alive, my lady!

[@SyntharaPrime]

Hello Mısra. I discovered you through your videos on AssemblyAI. Thank you for your fluent and comprehensible way of teaching. It is very clear that you put a lot of effort into the content. I wish you all the best.

[@misraturp]

Thank you so much for your support, Ilkay!

[@BigBrainHacks]

Love your videos! Please keep doing what you do...+10 karma points.

[@carlasanchez4349]

Thank you for this clear and short video

[@LadoKaladzeDev]

Short and simple Thank you !

[@efeincir3254]

Great and simplest explanation

[@bakaresegun4180]

You are really amazing ❤️❤️❤️. Please when should we use label encoding and one-hot encoding? And however, what's the effect of dummy variables in the dimensionality since it creates more dimensions?

[@bay-bicerdover]

not necessarily

[@smnomad9276]

Amazing content as always!

[@misraturp]

Thanks!

[@firat019]

Teşekkürler ☺️

[@misraturp]

Ne demek!

[@asfdsgfad]

abla ingiliççem yok şunları bide türkçe anlatırmısın