How he manage to explain something that a 1-hr lecture couldn't! Thanks mate
@BrianAmedee
4 жыл бұрын
'Clearly Explained' - and it actually was. Thanks man
@NormalizedNerd
4 жыл бұрын
:D :D
@pradyumnabada5118
Жыл бұрын
Dude.. I lost count of the videos I watched to understand this but lastly, after seeing your video the struggle ended. Thank you so much!
@bluestar2253
3 жыл бұрын
One of the best explanations I've ever seen!
@NormalizedNerd
3 жыл бұрын
Thanks mate! Keep supporting...
@jaster_mereel7657
3 жыл бұрын
This was a very clear explanation indeed. Thank you!
@NormalizedNerd
3 жыл бұрын
You're very welcome!
@sye9522
4 ай бұрын
HUGE thanks for perfectly delivering the whole concept in one video bro!!
@radoyapanic998
2 жыл бұрын
In the last part of the video you said we can fit a known distribution to a continuous set of data. However, you continued to then write that the probabilities can be calculated by taking the product of the pdf evaluated at different values of the feature and label. The pdf does not provide probabilities however, as it needs to be integrated to inform one of the probabilities of an event. This part of the video seems imprecise. However, the video in general was great. Thanks.
@RayRay-yt5pe
21 күн бұрын
You did good my friend. I'm glad I came across this video
@lakshuperiakaruppan6777
Ай бұрын
Good work with the visuals!!
@miusukamadoto6805
2 жыл бұрын
Thank you very much for the video. Clearly explained indeed, the only part I couldn't get completely was the discretization.
@noname-anonymous-v7c
7 ай бұрын
9:37 you made conclusion based on P(X=[0,2] | Y), I think the correct way is to calculate P(Y|X=[0,2]). In case P(Y=1) is very small, the answer can be Y=0.
@EduAidClassroom
2 жыл бұрын
LOVED IT!!! Awesome Explanation! Can't thank you enough...
@guangruli4486
3 жыл бұрын
Very clearly explained, thank you!
@sayonsom
Жыл бұрын
Great explanation :)
@jefersondavidgalloaristiza3410
9 ай бұрын
Very nice explanation and perfect illustrations!!
@imadeit6587
3 жыл бұрын
I am appreciate your work
@NormalizedNerd
3 жыл бұрын
Thanks a lot!
@high_fly_bird
Жыл бұрын
The explanation is so cool! But it would be even cooler if you added some examples with continious features and fitting a distribution, this part wasn't so clear...
@PritishMishra
3 жыл бұрын
If I search for any ML Algorithm I just first check your channel If you have created the video on the same... You are my first preference for ML/DL Algo Explanation. Just a request please make a video on Deep Learning Algorithm too like CNN, RNN & LSTM "from scratch". It will really help people who want to become practitioners in AI like me.
@NormalizedNerd
3 жыл бұрын
Thank you so much ❤ Writing CNNs and RNNs from scratch are pretty hectic...maybe some day I'll try.
@PritishMishra
3 жыл бұрын
@@NormalizedNerd Waiting... you are our only hope who can teach us Mathematics of ML with cool animation, That's why requested you! Thanks.
@mehditavakoli2492
Жыл бұрын
Thank you!
@aymericalixe1310
3 жыл бұрын
Maybe i'm wrong but I think the hypothesis is not that X1 and X2 are independant but that X1 and X2 are conditionnaly independant. It was very clear otherwise thank you !
@NormalizedNerd
3 жыл бұрын
In naive Bayes every feature is treated as an independent feature that's why it's called naive.
@chitranghosal879
Жыл бұрын
I think the hypothesis is that you assume each feature to be (w.r.t other features) 1) globally independent (in the global sample space) 2)conditionally independent w.r.t the occurence of each class label (under the subset sample space where the particular class event has occured) If these assumptions are not met, then it does not seem possible to build the mathematics, because as far as I see, if events A and B are independent, that does not naturally imply conditional independence between events (A|C) and (B|C)
@hasben0
Жыл бұрын
Well done👊👊
@DANstudiosable
4 жыл бұрын
Well explained, a quick revision for Naive bayes. I forgot why it was called Naive until i watched this video 😂😂
@NormalizedNerd
4 жыл бұрын
Thanks! Haha.
@dannysammy8972
2 жыл бұрын
Yes, this was actually well explained. Thank you :)
@daniilsukhovv
3 жыл бұрын
bro, best explanation I could find
@NormalizedNerd
3 жыл бұрын
Thanks bro :)
@dpaul3447
Жыл бұрын
Thank you so much man!!
@arielalvarez88
3 жыл бұрын
Really good work, congrats
@NormalizedNerd
3 жыл бұрын
Thanks man!
@SarahGhiyasi
Жыл бұрын
Thank u it was great.
@AnasHawasli
6 ай бұрын
Great video man great herre is a sub
@atulyadav9712
2 жыл бұрын
Great explanation
@muhammadzubairbaloch3224
4 жыл бұрын
sir please more lectures. I am seeing after too days later your lectures made some advance NLP and CV lectures or AI lectures thanks
@NormalizedNerd
4 жыл бұрын
I will try my best to upload more frequently.
@nikolai228
6 ай бұрын
Amazing video. thanks.
@prar_shah
Ай бұрын
Love this
@lucasqwert1
Жыл бұрын
in the last part at minute 11: What is the function f to fit a known distribution? Thank you for answering!
@MrDaniel560
Жыл бұрын
HELPFUL!!!!
@swethanandyala
2 жыл бұрын
very nice explanation thank you so much
@sopegue
2 жыл бұрын
It was clearly explained as mentionned in the title. Thanks a bunch !!!
@sobana653
Жыл бұрын
Nicely explained!
@aurorasart9458
3 жыл бұрын
Thank you very much for your work! Nice explanation!
@NormalizedNerd
3 жыл бұрын
You are welcome!
@sayantansadhu6380
4 жыл бұрын
It was like a revision for class 12 probability 😁😁
@NormalizedNerd
4 жыл бұрын
Yeah simple yet effective concept.
@adityaprasad3356
Жыл бұрын
very helpful🥺🥺
@user-or7ji5hv8y
3 жыл бұрын
Great explanation.
@NormalizedNerd
3 жыл бұрын
Glad it was helpful!
@leolei9352
2 жыл бұрын
Very clear explanation!
@user-wr4yl7tx3w
Жыл бұрын
This is really well explained.
@fmt2586
2 жыл бұрын
hey, thanks man, very clear explanation.😀😀
@joaomatheusnascimentogonca7633
2 ай бұрын
10:51 How does this work? wouldn't the probability that Xi = xi be zero, given we're using a continuous distribution? Because of the "=" sign
@parisaghanad8042
2 жыл бұрын
That was great! I'm really glad that I found your channel. Thanks a lot 👍👍
@dzmitryk9658
2 жыл бұрын
Awesome! Thank you.
@telusukondifirstuu9221
2 жыл бұрын
I love this Exolaination 😍🥰😘 Thanks a lot ❤
@quanghuynh1570
Жыл бұрын
you saved me
@nickgannon7466
2 жыл бұрын
well done
@sumedha1051
Жыл бұрын
love this!
@signature445
3 жыл бұрын
Sir is this like Bayesian classifier deals with conditional probability ? Naïve bays classifier deals with joint probability ? Thanks in advance.....
@NormalizedNerd
3 жыл бұрын
Yeah!
@aditya.singh9
3 жыл бұрын
truly amazing
@NormalizedNerd
3 жыл бұрын
Thanks!
@plumSlayer
Жыл бұрын
You areee Amazing. I love your Indian Bengali accent ( just a guess hehe make me a voice analyzer if i am right XD )
@mahirjain8898
9 ай бұрын
so goood
@Fuktron13
3 жыл бұрын
I wish you were my professor
@zouhir2010
3 жыл бұрын
thumbs up thanks
@kunalsoni7681
Жыл бұрын
Nice ⭐⭐⭐⭐⭐
@harshitdtu7479
4 ай бұрын
10:37
@xritzx
4 жыл бұрын
3b1b's bro is here
@NormalizedNerd
4 жыл бұрын
Haha :3
@Ilham-lj3me
Жыл бұрын
and how aboit gaussian NB?
@pushandeb187
11 ай бұрын
liked that
@abdulkarim.jamal.kanaan
3 жыл бұрын
Hello people from the future! :D
@anon_148
2 жыл бұрын
independant moment
@davidmurphy563
10 ай бұрын
Ok, I've given up on the video after 45 secs. You said "stated clearly", if you hadn't I'd have kept watching. You point to an array of features called X. What are they? Are they features of the array itself (its size / rank / dimension?), are they features of the thing the array of describing (measurements in a house?), or a list of possible attributes (the ingredients on a pizza?) Then you introduce a label. So what, is this like a python dictionary? Plus, I've no idea what sort of issue we're supposed to be tackling? Is it probability? Is it rationality with limited knowledge? I only guess that because I've heard of Bayes before. Instead you launch into calculations when I have not the first idea what you're calculating. Why would I listen to that? Tell you what, I'll give it another 30 secs. If there's no illustrative example / clear explanation of what the hell you're covering I'm gone.
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