Machine Learning Tutorial 10 - Binning Data

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[@chrismeni7462]

educative, simple, easy to understand - great job big thanks

[@stephenholmes9386]

This was just what I needed! I couldn't get my head around why some classifiers perform better after binning... Thanks

[@mayakali8356]

You sir are a gentleman and a scholar, My deepest gratitude to you and your ability to impart knowledge.

[@stephsharma2835]

Love the distinctions you make about getting information from losing information! Have you happened to find/use any academic references to support you/this process? (working on my thesis edits for social science paper - binned degrees of working hybrid)

[@siddhantsalve3363]

Thanks ! Best Explanation out there on YT!

[@prithivida]

You mean discrete (numbers) to categorical. Because age is NOT continuous (at least not in the abstract, age is used as a rounded number, even in the table you show it’s rounded). Temperature or any real numbered value like telemetry readings are examples of continuous numbers. 52.2 or 49.5 is continuous.

[@robindong3802]

Simple, easy and very educational. thanks Caled.

[@散华-l9m]

haha I even haven't think about learning my favorite machine learning during the exam, my interest and your style teaching may save my R language

[@johnchen5430]

Pretty good point; regression is also an alternative

[@Colstonewall]

Well done, Caleb. I'm enjoying this series!

[@Alex-ii3tv]

Great examples, sir!

[@ilhamakhyar4849]

Really thanks for the video!

[@pandiyarajana1666]

Hey buddy! Thanks a lot for this video... You nailed it....

[@ahmedelsabagh6990]

Simple and clear

[@KulbirAhluwalia]

Well done bro!!

[@josh83ification]

great explanation!

[@mob4681]

Perfect explanation

could you theoretically use a bell distribution around a certain age (say 55 years with a sigma of +-2.5 years) instead of creating arbitrary borders like everyone from 50-60 years?

[@doctorx2267]

Nice Content man!

[@davidnjoroge5705]

Mr beast is that you

[@raphaeldayan]

thank you!

[@jkl2142]

Great resource ! Thanks for it ;D

[@farazahmed6043]

lucid explanation

[@yessbenne5924]

I dony understund why you re calling a decision tree a data strcture

[@nickcalo7445]

Thanks Caleb! Your jokes had me cracking up as well.

[@Rainstorm121]

Thanks sir

[@RoshanKumar-nx6rk]

Those are above 50 who disliked this video!

[@debayondharchowdhury2680]

esoteric to layman perspecive

[@dzmitryk9658]

Awesome!

[@arashchitgar7445]

woderfull explaination. Thanks a lot man!!