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

@MaheshHuddar

Жыл бұрын

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Super explanation.. today is my machine learning paper

@MaheshHuddar

6 ай бұрын

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@ankitjha_03

2 ай бұрын

Mine is tomorrow!

@nurulsyuhadah984

12 күн бұрын

How was it?

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

@MaheshHuddar

Жыл бұрын

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

@MaheshHuddar

7 ай бұрын

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Super Bhayya ...

Thanks for the video. Great explanation!

@MaheshHuddar

Жыл бұрын

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

@MaheshHuddar

11 ай бұрын

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Excellent Teaching. Salute to you sir

@MaheshHuddar

8 ай бұрын

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

@MaheshHuddar

Жыл бұрын

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

@MaheshHuddar

9 ай бұрын

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thank u for uploading like this video

@MaheshHuddar

Жыл бұрын

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Clear and nice explanation. Thanks for the video

@MaheshHuddar

3 ай бұрын

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This man has depth knowledge of this topic.

@MaheshHuddar

6 ай бұрын

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Thanks sir for your explanation 🎉

@MaheshHuddar

Жыл бұрын

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

@MaheshHuddar

10 ай бұрын

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Thank you so much sir amazing explaination♥♥♥

@MaheshHuddar

Жыл бұрын

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Thats a clear explanation i have seen

@MaheshHuddar

Жыл бұрын

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thanks a lot for this wonderful lecture.

@MaheshHuddar

3 ай бұрын

Welcome! Do like share and subscribe

tq sir for this wonderful concept

@MaheshHuddar

6 ай бұрын

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thank you so much you are great professor

@MaheshHuddar

5 ай бұрын

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thank you sir, you were amazing🤩

@MaheshHuddar

7 ай бұрын

Welcome Please do like share and subscribe

Thank you very much sir

@MaheshHuddar

8 ай бұрын

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

@MaheshHuddar

2 ай бұрын

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Thank you very much master huddar❤

@MaheshHuddar

4 ай бұрын

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Thank you

@MaheshHuddar

5 ай бұрын

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thank u so much

@MaheshHuddar

6 ай бұрын

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

@MaheshHuddar

3 ай бұрын

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Thanks you,sir

@MaheshHuddar

5 ай бұрын

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

@MaheshHuddar

Жыл бұрын

Ensemble Learning: kzread.info/dash/bejne/l4Ktt8ipd6WypNY.html Random Forest: kzread.info/dash/bejne/nYSllZRxna20dZM.html

Thanks Sir

@MaheshHuddar

7 ай бұрын

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linear discriminent analysis please make a video bhayya

thanks a lot

@MaheshHuddar

Ай бұрын

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Excellent

@MaheshHuddar

4 ай бұрын

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Sir book name please

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

@MaheshHuddar

4 ай бұрын

You will get same answer with second equation You can use either first or second no issues

Nice!

@MaheshHuddar

7 ай бұрын

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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

@jvbrothers5454

7 ай бұрын

yeahh im also confused how did he get im getting values diffrent 0.3761 5.6928 -5.128

Why we are not dealing with e2 means why we not do e2^T.[cov matrix]

@rohanshah8129

9 ай бұрын

Here, we had considered 2 dimension as the high dimensonal data for example. One of the most usecase of PCA is in dimensionality reduction. So, if you want you can use e2 and get second PC. But then think about it. From 2 variable, we again got 2 variables. That's why he has shown only PC1. However, in reality we generally use 2 PC axes (mostly depends on your data). If it has a lot of variables, then 3 or 4 can also be good but we don't generally go beyond that. So, in this case you will need e2, e3 and e4 as well. So this is how it works.

Can you add the concept of hidden Markov model in your machine learning playlist

@MaheshHuddar

2 ай бұрын

Sure Working on it

@Blackoutfor10days

2 ай бұрын

@@MaheshHuddar okay 👍

@Blackoutfor10days

2 ай бұрын

@@MaheshHuddar my exam is near

Hi Sir, Great explanation about PCA. But when I searched the covariance matrix for more 2 variables it's showing that covariance is only done between 2 variables. How to calculate the covariance if a dataset have more than 2 variables. Could you please give an explanation on that.....!!

@fintech1378

Жыл бұрын

you need to do for all pairwise combinations

@shahmirkhan1502

Жыл бұрын

@fintech1378 is right. You need to do pairwise combinations. For example, for 4 variables, your covariance matrix will be 4x4 with the following combinations: cov(a, a) cov (a, b) cov (a, c) cov(a,d) cov(b, a) cov(b, b) cov(b, c) cov(b, d) cov(c, a) cov (c, b) cov(c, c) cov(c, d) cov(d, a) cov(d, b) cov (d, c) cov(d, d)

@rohanshah8129

9 ай бұрын

If there are n variables, covariance matrix will be of nxn shape.

@parthibdey6005

5 ай бұрын

is this covariance for reducing 4 to 1@@shahmirkhan1502

thankyou sirr, how to calculate 2nd pc?

@MaheshHuddar

Ай бұрын

Select the second eigen vector and multiply to the given feature matrix

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@MaheshHuddar

Жыл бұрын

What it means..?

@abishekraju4521

Жыл бұрын

@@MaheshHuddar According to google translate: _"I love you sooo"_

devru sir neevu

@MaheshHuddar

6 ай бұрын

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