1 Principal Component Analysis | PCA | Dimensionality Reduction in Machine Learning by Mahesh Huddar

1. Principal Component Analysis | PCA | Dimensionality Reduction in Machine Learning by Mahesh Huddar

The following concepts are discussed:
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Principal Component Analysis Solved example,
Principal Component Analysis Numerical example,
PCA solved example,
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[kenway]

I noticed that your channel contains the entirety of Data Mining taught at the Master's level! Thank you very much, subscribing immediately!

[ishu_official]

Super explanation.. today is my machine learning paper

[VDCreatures-kcuf]

Super explanation..the best channel in YouTube to learn machine learning and ann topics ❤❤

[TrueTalenta]

Amazing step-by-step outline!
I love it💌, so I subscribe!

[rodrigorcbb]

Thanks for the video. Great explanation!

[venkateshwarlupurumala]

Very clear Explanation Sir.... Thank you so much...

[kapras]

super explanation .. very easy to understand with out any hook ups sir
thanks ...Inspr KVV.Prasad

[thilagarajthangamuthu]

Thank you sir. Clear and easy to understand. Thank you.

[junaidahmad]

This man has depth knowledge of this topic.

[radhay]

Thank u very much.Very clear explanation and it is to understand

[NandeeshBilagi]

Clear and nice explanation. Thanks for the video

[HamidAli-ffzn]

Thank you so much sir amazing explaination♥♥♥

[Straight_Forward]

thanks a lot for this wonderful lecture.

[SaifMohamed-deuo]

thank you so much you are great professor

[ashishlal]

Thank you so much today is my data mining and ML paper

[yashtiwari]

Sir please upload the content of ensemble methods bagging boosting and random forest

[priyalmaheta]

content and teaching is very good please also provide the notes it will be helpful

[putridisperindag]

thank you very much Sir, for ur explantion on that video. I still confused so I would like to ask how to get the value of: [-4.3052, 3.7361, 5.6928, -5.1238] how can I get the value. I still dont get. Thank u Sir

[RaviShankar-gmof]

linear discriminent analysis please make a video bhayya

[nikks]

Hello sir, thank you for your explanation.I have a doubt at 08:17 why you have considered only first equation?