Math for Machine Learning | 5 L1, L2, L-inf, Lp Norm

A practical mathematical representation of data and what it means by L1 norm (Taxicab geometry or Manhattan Distance) , L2 norm (Euclidean Distance), L-inf norm, Lp norm, and L-0 norm

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[yelnady]

Finally, I understood the L infinity norm how it is transformed into just getting the maximum number.

[crackbreak]

Wow, the thing where you relate this boring math to machine learning, this is where you turn the magic on. I wished scikilearn had such an explanation in there documentation. Thanks

[didarulislamrifat]

Thanks man you are giving so much effort for educating us. I can only appreciate but I know it's not enough

[harshbhagwani]

can you explain that part again where uh took p=3

[kyang]

Thanks for the video, helps a lot in understanding of the L-p and L-inf norms! But I'm still a bit confused when p = 0 which is the L-0 norm. :(

[sahu]

Any real-time or usecase exist where p can be negative in Lp norm

[sangharshsharma]

Hello. How is the value of P determined here? How is it considered?