Lecture 8 - Principal Component Analysis

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Information Lecture 8 - Principal Component Analysis

Title	:	Lecture 8 - Principal Component Analysis
Lasting	:	13.03
Date of publication	:
Views	:	109 rb

wasted my 13 minutes 😒
Comment from : AP BEATS

Ma'am you should have completed the example you started with
Comment from : Singing Heart

Very nice explaination
Comment from : Arima Subbu

bkl galat galat calculation karii , tumhare bava correction karte??
Comment from : Eluri Sathwik

Last steps not getting kindly explain in simple way
Comment from : srinivas planing go 2 homerfr

nice
Comment from : MANOKARAN J (RC2113004011006)

In step 2 we only 10 value mam but you put 11 values?? how mam
Comment from : MANOKARAN J (RC2113004011006)

Very good explanation madam Thank you 🙏👏
Comment from : Akshitha N Y

Ma'am, which one is better PCA or SVD ?could you please tell me the reason?
Comment from : Prajwal KV

not good
Comment from : Amran Hossain

Worst video
Comment from : SAURAV THAKUR

You've just read out the algorithm Do you think it's gonna help us?? Atkeast you should've shown some calculation
Comment from : Satish Tyagi

why don't you show with an example
Comment from : dwaipayan10

Hey, great video, I learnt a lot if only 5 minutes with you, wow, I definately suscribe!
Comment from : Ulyses Rico Rea

Thank you
Comment from : gopi nathan

Nice madam thanks for the explanation
Comment from : M Ramesh

Thank u mam, nice explanation with formula
Comment from : Mahesh Kumar Velayutham

The fact that you showed the formula helped a lot, thanks
Comment from : Ahmed

step 4 missing? thanks a lot
Comment from : Muaadh_ABDO Al Sabri

You have started well but not landed safely You were in a hurry Explain the practical application with examples
Comment from : Saji Kuttan

Thanks mam brOne doubt brbrHow to find out the contribution of different variables in each principal components or all in all in final index
Comment from : vikash singh

Ma'am what is hotelling iterative methods for calculating PCA??
Comment from : Shubham Srivastava

Maam, you said covariance is relation between 2 axis, so when you took cov(x,x) how didn't you get 1I know by calculation its definitely 0616 but if you relate an axis to itself it should be 1I hope you reply to this messageThanks maam
Comment from : Frank Ribery

I lost at Eigen value
Comment from : Akshay Ak

Thanks for this video on PCA ,think u r CEGian,me tooo
Comment from : Sharan S

nice explanationThanks you very much
Comment from : Kamrul Hasan

Thank you somuch for ur in-depth explanation,i got fully information on PCA😊🤗
Comment from : Bhagya H B

Hi ,thanks for this easy to understand video on PCAcould you please do a video explaining tsne (t-distributed stochastic neighbor embedding)?
Comment from : Bala Murale

Good lecture madam, can u tell me which book are you referring
Comment from : Ram k

i have been searching for a simple and effective explanation on PCA for a very long time Thank you so much for the explanation may God Bless you
Comment from : Gabriel Lalchhandama

Lamda1 is equal to 005 not 05
Comment from : Mohammed Elhmadany

Best explained
Comment from : Sandesh Nangare

After step 3 I think you had no idea what's happening
Comment from : Raja kar

Can you please explain why we adjusted the data to pass through origin What happens if we don't adjust the data??brplease reply
Comment from : mohammed asif

you went too fast after eigenmatrix, could have understood better if used examples for explanation
Comment from : Vivek Shinde

thanks
Comment from : ismet öztürk

Whats this? many values are not explained
Comment from : Heaven Diver

step 4 missing ?
Comment from : Ani S

Ma'am I got confused in the theory after 10 mins
Comment from : Varsha Mehra

Very very thank you mam the video was very useful
Comment from : JCC MINISTRIES

You hand writing is very small please write clearly
Comment from : JCC MINISTRIES

Is your mean value correct?
Comment from : Shaiful Islam

Please take snap of this papers and make pdf and share the sameGood lecture Kudos
Comment from : Karthi Keyan

thanks for the video
Comment from : Shubham Chouksey

Thanks alot for u'r crystal clear explanation mam
Comment from : siri cherry

akka, can you teach me more regarding this topic ? I'm from tamilnadu this chapter is very difficult for me I'm doing Masters degree in anna university can you send me your mail id ? my maild id: stalinjune27@gmailcom
Comment from : Stalin Laska

Worst video
Comment from : ghanashyam gogoi

Its nice and Simple
Comment from : Kuppusamy Thangaraj

Thanks a lot mamworth watchingI watched few videos before this and read few articles n papers tooAt last u made me understand pca God bless you in all possible ways He canbrbrRegardsbrPooja- j&k
Comment from : Pooja Anand