1. Solved Example Naive Bayes Classifier to classify New Instance PlayTennis Example Mahesh Huddar

[@MaheshHuddar]

It takes a significant amount of time and energy to create these free video tutorials.
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[@KarthiDreamr]

It's really hard to match your time efficiency , awesome explanation

[@jenishshrestha8613]

again some random dude helping me for my finals , op video

[@talibdaryabi9434]

Finally, I found something great for a better understanding of Navie theories. Thank you.

[@MaheshHuddar]

Welcome
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[@NitinSharma-qx4ff]

NAIVE* not navie

[@krishnaa5351]

Most complicated teaching, waste fellow

[@amoghsinha4305]

Explained better than my university's professor

[@MaheshHuddar]

Thank You
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[@nadeemhussain4080]

Beta class kiya karo University's professor bhi acha padhate h

[@special2388]

Infact,You weren't attentive in the classes.

[@abeeranaeem7127]

Us bro us

[@Krishna_Singh_2111]

To University jata kyu h yahi padh le

[@strydomobile]

I like your way to teach, simple and conceptual. I find most people try to sound smart the whole time at the cost of carrying the message over efficiently. Thank you for this video, its clear simple, and to the point.

[@MaheshHuddar]

Welcome
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[@malanosi2869]

sir our very much reputed college is making ppt by taking screenshot of ur videos and also making question paper using ur videos.
100% usage of our parents hard earned money by the college

[@SiddharthGargYT]

lol

[@mohitx3g]

😢😂

[@ShivamPanchbhai]

God bless you
you are much better than my college professor

[@jaygupta4214]

are u god or god made me found you at the last moment ??
no faltu bakwas kaam ki baat delivered in accurate way

[@MaheshHuddar]

Thank You
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[@jayanthychakrapani3553]

I really found your video very useful for solving my Homework questions sir, but I was really hoping if you can explain the terminologies in this question : "hobby=tennis ^ good-hacker=yes ^ has-publication=yes", Thank you very much!

[@sharaniloganathan9]

Explained very well sir........ U people r the reason to pass students like me who r studying one day before exam... Thank you so much

[@mitheeleshkatyarmal8159]

Top class explanation, Every minute explained in this video is worth hours of explanation.

[@MaheshHuddar]

Thank You
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[@rishabhmishra279]

you have explained in a very simple way and intuitive ! thanks a lot.

[@MaheshHuddar]

You're most welcome
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[@ritwickghoshal91]

Exactly point to point, Thank you, this video helped me a lot.

[@MaheshHuddar]

Welcome
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[@melaniemurday3138]

Thanks a lot for providing better explanations than my lecturer.

[@MaheshHuddar]

Most welcome!
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[@letsgo2793]

Your Teaching way is actually so good

[@MaheshHuddar]

Thank You
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[@callofdutysuperheroes]

Sir are you serious, how you understood that this is the most accurate way to teach , love you sir ❤

[@MaheshHuddar]

Welcome
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[@wjrasmussen666]

Best video explaining this on UA-cam. Love it. I subbed.

[@MaheshHuddar]

Welcome...

[@gudurilakshmi3886]

Even our professor uses ur vedio in his ppts😂🙏

[@MaheshHuddar]

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[@topicblogger377]

Are you from Amrita Vishwa Vidyapeetam 😂😂

[@trendingstatus1398]

Yes my professor too😂

[@s0lanav]

Thank you sir for your very good explanation, helped me a lot.

[@herosoftheworld7]

Explained better than meticulous teachers🙌

[@ayushtiwari2009]

Thank you so much sir for this wonderful video, my university professors should learn from you how to teach and deliver in a proper way so that the students can connect.

[@MaheshHuddar]

Welcome
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[@hossainalif3909]

Thank you very much sir....
I was so confused with naive biase.....
This video cleared all my confusions......

[@MaheshHuddar]

Welcome, glad it helps you
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[@shabeeb4002]

outstanding explanation sir , really appreciated . thanks a lot for giving us such a wonderful explanation . Keep going 👍👍

[@MaheshHuddar]

Thank You
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[@iniyaviji2796]

Sir super super am very much satisfied.your explanation is very clear.god bless you sir thank you my teacher

[@MaheshHuddar]

Welcome
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[@eesabkhan]

Wow. You definitely know what you are doing!

[@pauljohnson6844]

Thankyou for the video, This one is the best video I saw for Naive Bayes , Explained it very simple

[@MaheshHuddar]

Welcome
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[@ehtisham_hashmi]

@@MaheshHuddar 0.0053 kesy aaya 6:10 py

[@govindjangid6201]

Thanks sir.. very well EXPLAINED 😊

[@mazzideno]

Well explanatory ❤❤❤
Somewhere in Nigeria

[@MaheshHuddar]

Thank You
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[@kayenatsabir1811]

exactly i had watch more videos navie bayes but cannot understand now u are one that i can understand

[@MaheshHuddar]

Welcome
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[@mkjilani]

Thanks!

[@MaheshHuddar]

Thank you for your Support
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[@gauravghosh6562]

what a legend this person is.

[@MaheshHuddar]

Thank You
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[@sweetcadbury]

Excellent explanation. Thank you Mahesh

[@MaheshHuddar]

Welcome
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[@hlgsagar3792]

Understood clearly sir, Thnk you so much

[@tahminaakter4749]

Nice explanation. It's very easy to understand for beginners.

[@MaheshHuddar]

Thank You
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[@fatimaiqra2169]

Very exact and to the point explanation...thanks

[@MaheshHuddar]

You're welcome!
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[@ziedboughanmi4345]

Shih meksh haddar barsha ama tbarkallah aalik taaref tfasser khir ml moudir mtaa el fac mtaana

[@ramankumar41]

Sir your explanation is very good !!!!

[@MaheshHuddar]

Thank You
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[@mohammedsadiq69]

Bro..Vera level🔥🔥🔥

[@MaheshHuddar]

Thank You
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[@fashiononyourway]

Keep making such useful videos sir.I understood clearly, thank you so much

[@Aziz0.]

I was hoping your videos were arranged in ascending order to make it easier to locate each one.

[@RaushanKumar-iw5dn]

Sahi bole bhai... professor kya pdhate pta nhi... ye video dekha kr smj aa jata hai concept kya hai..

[@farhana339]

Thank you so much sir.... ❤️It helped us a lot

[@aparajitasingh690]

Thank you for the video sir. Great explanation !

[@MaheshHuddar]

Most welcome!
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[@data_analytics_study]

Very clearly explained sir, thanks

[@sandlinjames]

Very good walkthrough; thank you.

[@MaheshHuddar]

Welcome
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[@seethaselvam7969]

Thank you so much sir🙏

[@Crypto-vp8e]

P(yes) p(sunny/y) in dono ke bich mai kya krna hai? Multiply add or subtract?

[@a47ashishsingh76]

Multiply

[@tafveezahmad9692]

YOU SAVED MY EXAM

[@tafveezahmad9692]

THANKS ALOT

[@G.keerthi544]

Hi did you pass machine learning exam

[@tafveezahmad9692]

@@G.keerthi544 yes

[@G.keerthi544]

@@tafveezahmad9692 ur jntuk haa

[@tafveezahmad9692]

@@G.keerthi544 no

[@rawushzafar2735]

thank you sir! from Afghanistan

[@MaheshHuddar]

Welcome
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[@neggaznabil7570]

Great thanks for your explanation. I have a question: how you can classify a quantitative variables (NUMERICAL values)with NB?

[@MaheshHuddar]

Are you talking about continuous valued attributes..?

[@neggaznabil7570]

@@MaheshHuddar yes about continues variables. I think Gaussian naive Bayes will be applied in this case!!

[@Jash20243]

Sir you are god,god is great.

[@MaheshHuddar]

Thank You
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[@raghuvardhansaripalli9636]

Sir namaste, superb video sir. Thank you so much. I have shared this video to my friends

[@HariniKaran]

Salute sir tqsm 😭💓💓💓💓

[@mychannel-dg4oc]

Preparing for my exam at the last moment with this video's help ,rather than my class notes 😅

[@muskansanglikarmss9101]

Explained in very simple way..thanku sir🙂

[@shivamtiwari1897]

sir, you made it very easy to understand

[@MaheshHuddar]

Thank You
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[@citizen3624]

Thank you Sir..clear explanation..

[@MaheshHuddar]

Welcome
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[@kvancadguzel205]

Sir,thanks for the amazing video its so clear. Which book do you use for questions&examples?

[@testaunni1284]

Excellent explanation

[@MaheshHuddar]

Thank You
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[@kitchu_chinnu_stories]

In this example you done the normalisation but in example #2 not done ?why?

[@mvikramaditya8264]

@ 4:37 Getting different answer sir for Vnb(yes) Getting 0.0053 and vbn(no) Getting 0.0205 sir

[@mvikramaditya8264]

After normalizing I am getting correct answer sir Thank you great explanation

[@MaheshHuddar]

Welcome
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[@ReshmaA-wh5us]

Aioo nigalam illana nagalam arrear than tq so muchhhhhhhhhh

[@aryasonawane4148]

Best wonderful 😊💯

[@MaheshHuddar]

Thank You
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[@VinayGupta-mf1js]

Sir please, it is wrong answer....because ques given solution only sunny cool high strong...

[@bilalillahi6347]

Wdym

[@anaymehra7630]

No it is correct

[@karthik-varma-1579]

My college done 100 subs today since today is exam

[@SaileeShingare]

Great explanation. Thank you, sir

[@wanderkidtraveler7429]

⚠️⚠️

[@msai4856]

Another great.....

[@MaheshHuddar]

Thank you
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[@laibaajmal6908]

wowwww amazing, thanks a lot sirr

[@tejasvinnarayan2887]

What if temperature and humidity is real? Like their values are given and there cannot be any logic derived from the dataset?

[@mumbaikachallenge5526]

Absolute amazing sir

[@MaheshHuddar]

Welcome
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[@ashmitshelke1444]

why are we calculating the probability of overcast / cool /humidity=medium, if we dont need it while prediccting?

[@Kritheeshwarb]

In the end shouldnt it be divided by P(sunny) * p(cool) * p(high) * p(strong) . i.e p(new instance)

[@afreenoorul21]

How to calculate vNb(yes) = p(yes) p(sunny).... P(strong)

[@divyangmathur]

thanks sir helped a lot

[@MaheshHuddar]

Welcome
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[@sunnyysn5434]

kcpd explaination bro !! luv u

[@anirudhshankarkhedker4400]

(Outlook=Sunny, Temp=Cool, Humidity=High, Wind= Strong) sir is this condition took randomly? or is there an algorithm to take these conditions?

[@chiragjain291]

It will be given in the question (It is like a test set so it tests that for the given set of attribute values what will be the prediction?)

[@aunekhan3794]

Randomly

[@jaideeprathee5951]

This is the question

[@islemsahli737]

you are amazing thank you!

[@MaheshHuddar]

Welcome
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[@mohammadmahbubtalukder3824]

thanks man, great job

[@MaheshHuddar]

Welcome
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[@nature..1787]

amazing explanation...

[@MaheshHuddar]

Thank You
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[@estherr7931]

my life saver fr

[@MaheshHuddar]

Thank You
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[@abdullahmohan9107]

good explanation sir.

[@muhammadgulzaib7567]

That was sooooo easy man, thanks

[@ahmarhussain8720]

excellent explanation

[@lekkalaakhila5257]

Good explanation sir

[@theblacktoe]

helped alot. thankyou

[@trivenimarlapati9857]

Tq u so much sir👏👏

[@Anitha2076]

How to calculate the VNB yes( values)

[@shaikhuzma786]

Tqsm sir❤

[@MaheshHuddar]

Welcome
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[@karunanithik1584]

Do we have to multiply all the probablites

[@ibtehazahmad]

Thank you so much

[@MaheshHuddar]

You're most welcome
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[@abhish8867]

very greateful to u sir

[@harikrishnajiju2131]

Thank you! Very helpful :)

[@MaheshHuddar]

Welcome
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[@HARSHRAJ-gp6ve]

Well explained

[@MaheshHuddar]

Thank You
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[@beingasif1279]

Condition is given in question or we can make it our self

[@hayafatima9844]

Dil to krta ha degree bi UA-cam sa hi lay lon university ka nam ka to thapa lagny jaty hn baki youtube e UA-cam sahara ha

[@HaRa3038]

Perfect 💚

[@MaheshHuddar]

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[@soumyabajpai466]

it was very great !!

[@MaheshHuddar]

Thank You
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[@SujeetKumar-tl3lq]

On youtube various beggars are throwing ads, share some other medium to be in loop..

[@MaheshHuddar]

..?

[@vijayalakshmip6963]

Outlook sunny 2/9 for yes then for No also it should be 3/9 rt could you pls explain

[@Adilkhan-lm6ic]

No. We have to divide the total number of no's and yes's in the data . Total yes=9 and total No=5

[@MohammedAli-p7e9d]

So we normalize the values of V(yes) and V(no) so we add them.
If the result of the summation = 1: Our solution is correct.
Else:
Our solution is false.
Please help me...

[@MaheshHuddar]

Sum of normalised values should be 1

[@MohammedAli-p7e9d]

@@MaheshHuddar Thanks Sir!

[@HARI5H.S]

Hey did u multiple the values fr yes nd no instance?

[@anmolgoyal6010]

sir we need to calculate vNB(yes) and no at last step this point not clear