Tutorial 48- Naive Bayes' Classifier Indepth Intuition- Machine Learning

Guys there were some issue in the previous video. So I have reuploaded it. Sorry for the trouble.
In probability theory and statistics, Bayes' theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event
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[@kpratik5551000]

Superman, Batman, and Iron man of the data science.

[@munjirunjuguna5701]

Your zeal and energy is contagious...I am grateful for the work you are doing! Such an amazing teacher you are!!!

[@melvingeorge5770]

Huge appreciation for the efforts you put in simplifying and explaining the working of Naive Bayes algorithm. Really loved the video. Thank you!

[@anushapinniboina7931]

I always wander how can you make it so easy for the Non IT grads like me, you are truly an inspiration . My Best wishes for your upcoming projects

[@raghavendra2096]

There is nobody that can teach an algorithm this deep as you do, thanks soo much sir. I am really thankful to every content that you are posting, i am doing my PG and every time i complete a content there i come straight here and complete this to make my self very clear about the algorithm.
There are times where i dint understand certain portions in my class but you were the one who cleared it. These contents in your channel are worth soo much!!!!!
Looking forward to attend mock interview in future :) :)

[@archilshah9530]

This particular video is exceptional. Thank you!

[@kunalmalhotra7060]

Great sir, a huge appreciation to your work that you are doing for us.

[@preetibhatt5085]

Really nice , informative and elaborative . We are very thankful for your efforts . Entire student and working community will be greatful for your efforts today and in the time to come . Request you to please provide indepth intuition for xgboost also

[@panchammahto7837]

This was as simple and effective as it could have been. Neat..Clean and Precise👍

[@somalkant6452]

Thank you krish. you are touching the right pulse of the students / learners. you can very well understand in which areas the people might be struggling for understanding the concepts. Lots of my doubts are getting cleared watching yours videos. Thanks a ton. god bless you. stay safe.

[@adarshsharma8039]

There are other videos on this topic where people have talked nonsense, but you have explained it perfectly.

[@josericardo8102]

Thank you Krish! Although this example is very common in websites, videos and books, I have never seen before a complete step by step calculation and conclusion. You did it very well ! Great.

[@sagarhire8228]

Fundamental assumption in Naive bayes is that, it consider "Features are Conditionally Independent " . and therefore we can obtain P(class_lable | X) is directly proportional to P(class_label) * ( multiplication of individual probabilities of xi(features) given class label) where xi belongs to query point

[@DeepROde]

It's so fundamental that it's perhaps the first line I'd remember about Naive Bayes Classifier, surprised that it hasn't been mentioned.

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I must appreciate your zeal and relentless effort to teach others. You are an amazing teacher.

[@sinapoly]

This guy deeply understands the topic and what he is talking about. Bravo Krish!

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I can images how much hard work you did for preparing contents for this video, it's amazing i understood it by watching 1st time. thanks for making this.

[@zaheeraslam6920]

For years I was wondering here and there , and Finally I got it through this video, Thanks a lot

[@SunnyKumar-tj2cy]

Thanks for re-uploading it sir, last video had blank portion. Thank you for your effort in these times, stay safe.

[@souravbiswas6892]

Hi Krish, this is one of the best Naive Bayes video I have seen so far. Excellent job

[@TheVerbalAxiom]

This was a perfectly simple and to the point explanation. Much appreciated!

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wow man this person puts his heart soul for teaching great work

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I cant stop thanking you ! you have made it pretty easier ..

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This comment is intended toward your previous Bayes theorem video, "you are so fine when it comes to teaching statistics and moreover about data related studies" great going big bro.👍👍👍

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I am from life science background,far away from mathematics. But the way you have taught this topic each and every concept became crystal clear in single watch.

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Great video.. The way you explain and detail these topics - really appreciate it. Thanks

[@surbhisoni5614]

Thankyou for such an easy and nice explanation Sir, the way you teach makes our concepts crystal clear. Thankyou for so much efforts.

[@heller4196]

This is good for quick revision for interviews.

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The way you teach us make complex things to so easy, understanding....:)

[@Vinay1272]

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[@tejaswini07j]

Thank You so much! Finally understood this after surfing the net for half the day.

[@UniversalFacts-unknown]

Making difficult things so much easy. Thanks Krish

[@karanwadekar3392]

Thanks for the explanation. I think in the expansion of the Bayes formula for the data set, we have to use the conditional independence assumption. Only then the joint distribution can become relatively simpler to deal with.i.e all features are conditionally independent of target/output variable.

[@ksbaboo]

Good and Clear explanation with example.

[@sudhanshuparab198]

Amazing video bro , very good for understanding the intuition behind various algorithms used in classification thank a lot

[@ATothFTW18]

Fascinating! Great teaching!

[@shahrukhahmad4127]

I always follow your videos to get the concepts in a systematic and easy way, thank you Krish sir.

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Thank you so much for such a beautiful explanation.

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Hats off Sir, you made it easy,, Actually very easy....!

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You've made it look simple and easy to understand. Thanks Krish

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I always say proudly to my friends that i'm student of krish naik .Really explained in great way ...Thank you !

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Great video. Your explanation is easily understandable. Thank u so much for providing all this free and open source

[@TechnicalAnkesh]

Thank you so much sir you explained this concept in a very simplified manner I really appreciate your efforts

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Well explained sir, Thank you so much for teaching us!

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Just wanted to say I love this channel

[@carloschire5777]

Absolutely fantastic!!! very clearly your class, thanks a lot Krish

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@KrishNaik your videos are very precise, to the point and beautifully explained

[@a4alfiya]

It was a very good session... Watched your previous lecture also... Hats off 👏👏

[@bhumikasadhwani6109]

Your explanation is commendable sir ✨, thankyou.😊

[@SandeepTiwari-kz6xe]

Explained in best way.

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Finally I could understand by this video. thank you so much. you are great

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Thank you sir!
You explained it so well!

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Clear-cut explanation sir. Thanks a lot for the video

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Fire! Looking forward for more in ML and AI

[@adityashidlyali5751]

Awesome sir loved it..❤️

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Good explanation of the concept. Crisp and clear.

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Thanks a lot krish.. All your videos are helping us a lot.

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Thanks Sir G for great revision.

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pele like karneka fir video dekh ne ka.........ha aur intro bhi kadak tha

[@rishabhupadhye594]

Sir Hats Off to you. The efforts you are taking is phenomenal.
Yours Sincerely,
Future Data Scientist

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Great explanation! Thanks!

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Mind blowing sir, really mind blowing ❤️

[@alenskaria4054]

Thank you, sir
Got something in my head about how to apply for prediction

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Bundle of thanks sir ❣️

[@saranyanithyananthan]

Amazing Explaination!!! Thanks so much !!!!

[@plogramer]

Very helpful to understand Bayes concept! thanks much!!

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Thank you sir..........................you explained it so simply.

[@pradeepkumarsingh5359]

That's a superb explanation Krish...Thanx a lot for this..

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Amazing teacher , explain every topic very easily

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you are the inspiration for all of us god's blessing..

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It is amazing to watch you video. I really appreciate the way you present. I wish you would show us the original data in this case.

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amazing sir, the efforts that you put in are superb

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Awesome explanation...Hats off 👍🏻👍🏻👍🏻

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Amazing video sir!

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Very good sirji ,all the best.......

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Excellent explaination

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Really Really Good Explanation

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Great Work

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U NAILED IT BRO

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Awesome explanation.

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awesome explanation

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Thank you Krish 🙏

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Thank you for explaining the example sir

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I really liked your teaching

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Many thanks for simplifying

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great job for beginners...

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thanks to you I had to understand it well.

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Excellent.

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I am regular visitor to this channel 👍👍❤️