Hindi Machine Learning Tutorial 16 - Principal Component Analysis (PCA) with Python Code

[@codebasicsHindi]

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[@devang.danidharia]

Thank you sir to making videos in Hindi Language.. Now i understand PCA perfectly.

[@ashishzine14]

Amazing tutorial sir

[@akashgayakwad8983]

I wathced very first time machincelearning video , nice lecture

[@codebasicsHindi]

Thanks and welcome

[@deltaelectrocode4417]

Excellent sir. Please make one video on factor analysis.

[@rb4754]

Informative

[@rb4754]

Amazing

[@devanshgoel9070]

thank u sir

[@AbhinavKumar-dr4ef]

Thank you.

[@arshad1781]

Thanks

[@Sanaullah-ok5nr]

#Question: Sir in tutorial we passed unscaled DataFrame X to PCA i.e pca.fit_transform(X) for 95% info, and from 64 it reduced to 29 components. fine! ... BUT .... when i give scaled_X (transformed by StandardScaler) to PCA function for same 95%, it reduced to 40 (instead of 29 or less ) for same 95% important feature information.
I was expecting more reduced for standardized DataFrame. Please explain. Thank you !

[@parulchoudhary629]

hello sir... please make videos on biometrics data

[@rb4754]

Nice Video... 🥰🥰🥰🥰🥰🥰🥰🥰🥰🥰🥰🥰🥰

[@avneeshkaushik6474]

Sir playlist pura kijiye

[@hhamzazaibbhatti1765]

kamal

[@mahadevagra]

COULDN'T UNDERSTAND HOW CONVERRT PIC INTO CENTRAL PIXEL AND CORNER PIXEL.

[@deepakkumar2078]

R STUDIO m btao PCA

[@VishalMalik2023]

pca = svc.score( ) they predict best score 72%

[@ajmeershahtricks6666]

sorry sir im uable to solve excercise i visit solution link but still im unable to understand the code and logic as well sir if you make a video on the excersise it will very helpful for us