Guys just a small change int he formula p(b|a)= p(anb)/p(a) .please consider this change

@ 4:05, it should be probability of A event as 2/5 (bcoz you have defined A to be the event where you get black marble) @ 6:15, in the formula in the denominator it should be P(A) Also one small thing which should be mentioned is that in Bayes theorem the events must be mutually exhaustive (that is the whole sample space is partitioned into events)

Seen lot of lectures of your sir. But writing it first time, sorry took time for commenting, but thought guys like you must be appreciated for your efforts and helping data scient enthusiast without any cost. You make things very simple to understand and to the point. Appreciate sir. Really...thank you

Your are the man, you such a gem in youtube thanks brother for the video

Thanks, It's a good explanation; but I think the reference of P(Event A) and P(Black) is slightly confusing.

How did you know that I was searching for this? I was just searching for this topic on youtube, and at the same time, youtube notified me that you have uploaded a video on it.

Very informative . I am very thankful to you .. You are source of inspiration for students and working professionals . I have been following your channel for quite long time. Pls make video on maths intuition on gradient boost and Xgboost . Your ML playlist has video on ADaaboost but not on former two . Thanks again for your selfless efforts 🙏🏻🙏🏻

In 6:46 you took p(b/a) =p(anb)/p(b). , But later at 7:30 while deriving, your taking p(a/b) =p(anb)/p(b). That's a mistake. You actually changing the formula.your wrong there.

Love the new intro! Did you make it yourself?

INTRO was dope bro....👍👍☢️

Hi Krishna, I have been following you since last year. Your videos are very informative, concise and helpful. My comment is not related to this particular video but in overall. I do have a request to you for a video answering the following question: how the cost function for logistic regression differs from the cost function used for typical linear regression. In both cases how does the calculation of parameter values depend upon finding the minimization of the cost function?

Sir, please make a video on Gradient Checking and Adam optimizer in the Deep learning playlist. Me and most of my friends are waiting for that.

U really deserve to be good teacher

Thank you sir! It's clearly visible that you are really teaching by heart!

I love u seriously..u r the best

Great video, Krish! Explained much better than by my well paid lecturers :)

Oh man, you are really awesome. I just came across to your videos and found it very easy to learn. I like that you have created short videos for each and every topic which is way easy to learn. I really appreciate it Sir. amazing work. Subscribed and liked it... will continue to do so and I hope you will be teaching us.. Thanks you Sir Naik.

Hello sir. Your all lectures are very helpful and understanding. Thank you for making such tutorials.

Good Video. Bayes theorem simplified

Thank you. I understood this today only

but both events are dependent why did you perform p(A intersect B ) ??? ... event A and B multiply if both are independent ??

this guys intro is FIREEEEEE

This video is amazing, incredibly helpful.!!!!!!!!!!!thank youuuuuuu

Much informative❣️...will recommend your videos to our students also.

thnak u so much sir ur teaching is so clean i am so satisfied watching this

Hi Krish , It is good explanaton. But i think as you showed one example of conditional probablility, Same way one example could be added on Bayes' theorem (Which also called reverse probablility)

I'm new on seeing this video I like the way of u r teaching sir

Thanks for this video krish.... Can u please make one video explaining terms like Maximum likelihood estimation, Log of odds, logit function...plzzz

Very well explained. Thank you.

Excellent way of teaching Sir

Thank you so much

Great explain sir. It is very helpful to me.

Incredible teaching ....

Thank you sir

Great explanation Krish.Thanks

Thanks a lot dear sir love u

everything got messedup because of the naming convention, point - A, B are events, try with different names , so it won't get mix with P(B) which is probability of getting a black ball. ps - rest everything is very smooth, thankyou so much sir for the video xD.

Krish, Thanks for sharing. Can I some information about how should I choose an best algorithms before the start of machine learning. What sort of things I have to evaluate before working with an algorithm

Lovely explanation bro ! Thank you !

Bro can you make the playlist for all tutorials and for mathematics for ML/DS

Really helpful! Thank you❤

excellent explanation.

Eagerly waiting for next one..

Probability of Black P(B) is getting confused with Probability of event B. P(B)

Well explanation bro.

Sir please help me in understanding that ... P(B) event that is 1/4 when there is 1 black marble out of 4. And P(B|A) is also the same scenario when A event has occurred and we r having 1 black marble out of 4 marbles. Then how we will differentiate between the two. As we have done P(A)*P(B)=2/5*1/4=1/10

excellent explanation

What is the best data science course or certificate out right now? Nice video btw

Good explanation though there are some mistakes. Like the formula you give 1st and telling intersection as 'and' and later as 'or'

Very thank you sir 🙏🏼

Sir mechanical can do data science

Hi, Krish. Are you removed the NLP playlist ?

New intro 👍

Awesome job Krish.... Nice to see your videos... Great Work... Remember me from PUC , Philos?? :D

Super sirrr😎

Hey Krish I have a problem I am using a large dataset and it takes hours on my laptop When I use Google colab it keeps on disconnecting after something Any suggestions

I have a confusion in while solving an example since we were using bag of words we get some probabilities for each word in that stuff Sir, please clear me that with an example how it works plz

What is difference between conditional probability and bayes theorem.

Hey please upload videos on SVM & Hinge loss.

Sir i am also waiting for SVM video please upload it

In 5:00 min, did you mean the b in p(b|a) as event or probability of picking up a black ball?

there is no such thing as dependent events merely because something depends upon other unless it has some meaning . Even to be called for independent there should be something to be depend on. i mean you can not put the demarcation between dependent and independent. even dependent events use the independent theory (multiplication theory). for example, a man of eighty has less chance of surviving than a healthy young man. probability is dependent on his age. but the probability of his infatuation of woman is likely to be same even though chance of infatuation depends on his age(in this case). while computing this probability (infatuation) you use the independent formula to the dependent one. for the sake of linguistic purpose, yes you can. people have misunderstanding about it. independent events is mathematical but dependent is just a word in English. i have never seen any book quoting about the dependent event.

Coolest Intro I have seen in a while!👍🏻🙏🏻

Sir conditional expectation also please

Can you also please explain Bayesian regression models?

Awesome sir

Excellent...

When can you teach on Bayesian Neural Network please?

6:26 is wrong. It should be p(B|A) = p(B n A)/p(A) not p(B|A) = p (A nB)/P(B)

This is confusing. He says that P(B|A) is 1/4. But for him event A is taking a black, and B is taking another black. Shouldn't it be P(A|A) = 0.25. Very confusing.

In fact, be very careful with the explanation made, is a good one but, Krish, unfortunately, used the same laters in "even B" and probability of taking a black p(B), their fore in his explanations sometimes he uses p(a) = probability of occurring the event A, (min 6: 25), the p(B)= 2/5 is for him the probability of occurring the first event, taking a black (B) = event A.

Sir, SVM Kernel Intution video is not available on your youtube channel.

at 7:10 you are saying P(B/A) = P(A intersection B)/P(B) but at 7:25 you have written just opposite, which one is correct ?

it tricky as to how you define p(A|B).....we know P(B|A)...but we do not know what P(A|B) means with respect to picking black marble.

really goooodddddddddddd

Tqq ❤️ a lot ❤️

Intro 🔥 🔥

You should edit the video where it is acclidly wrong.it is. Confusing.

Can i say that, always - conditional probability is the probability of dependent events ?

I am waiting for SVM for classification and regression...

It's always good to learn something new. However, when will I really use statistics? Simple themes of math such as addition and subtraction multiplication division etc. I use almost everyday.

Plz upload support vector machine

the problem i find in this lecture is that , the Black B and Event B make us confuse

Engineering?????

Pls reduce the volume of intro bgm

nice

intro music name ?

It's 1/5

dont get nervous baby

You did nothing but confused the theory

Your math is WRONG!

wrong padhra lge ho

Thank you sir