WOW! such an explanation, sir your explanation is on 6 standard daviation, keep it up. This field is getting even more interesting for me because of you sir. Thank you!
I haven't seen such an in-depth video about statistics that could relate data science in such an effective manner ... I have been watching statistics from so many teachers but couldn't relate how statistics is utilized in data science But now things are getting cleared ...
I dont understand why have we divided by 2? The explanation : because it is combination of 2 graphs, doesn't make sense either. As per my understanding we wanted decaying property of e^(-x) and a graph symmetric on both side of x=0. Hence the square => e^(-(x^2)). Then scaling and shifting happened. Hence e^(-((x - mu) / sigma)^2
mera teacher paid course ka sir ka contant same copy krta hai. balki kar bhi nahi pata ache se. or dusra sir ki mehnat ko khood ki batata khood pta ni lgta. or kehta hai ki one of my intern ne project bnya hai. jabki wo nitish sir ke intern ne bnaya tha
generally Mode < Median < Mean for positive skewed distribution, but if the data values are huge near the peak then mean will shift towards left and mean may becomes < median in that case right? I checked, this happens, I just wanted to confirm from you that this understanding (Mode < Median < Mean) is not all true right for +ve skewed? It may depend on the data points.
Sir jab hum max range ikal rahe hai to outlier check karne k liye to apne bha pr mean nikal kar 3 std se + kiy bo ku kiya Agar hum normally 3 std nikal le tab bhi to bo max value bata dega na + karne ka kya logic hai pls btayia
U r a great teacher. I have not seen anyone with so much of in-depth knowledge.
You are the Don Bradman of Machine Learning field.
Couldn't be a better analogy, i 100% agree.
Wish you to get 75lakhs subscribers soon. Your efforts , quality of teaching and humility deserves that.
humanity not humility 😁😁
WOW! such an explanation, sir your explanation is on 6 standard daviation, keep it up. This field is getting even more interesting for me because of you sir. Thank you!
I haven't seen such an in-depth video about statistics that could relate data science in such an effective manner ... I have been watching statistics from so many teachers but couldn't relate how statistics is utilized in data science But now things are getting cleared ...
OMG. You're extremely amazing. Every video of yours is so helpful and detailed. Please keep sharing your knowledge.
Thank you !
1:07:08 - standardizing data
1:50:40 - finding outliers
i wish my collage teachers can teach like you , first you clear every basic and fundamental things and make very hard topics like a piece of cake
Well said
Congratulation for 75k mark. Looking forward to 100k soon.
Gr3at! How can I appreciate you I have no words
Thanks Sir for this quality teaching which was missing in our college education.
Really amazing session, this video has cleared all my queries . You have explained very well.
thanks for valuable insight..........................loved the seesion!
Not a single person gave me such deep intuition about the formula of normal distribution.
Greatly explained Nitish Bro!❤
thank you so much
great lecture sir ji ....as always great ..........❤❤❤❤❤❤
I have no words for your teaching. I'm confident for taking placement in the data science field just because of you sir 😊.you are the great one 🎉
Thank You Very Much Sir.
Happy Ugadhi sir
---- from Siddhartha Bangalore 🙏🙏❤️❤️❤️🙏
Vry good explanation sir❤❤❤❤
GOAT
I dont understand why have we divided by 2? The explanation : because it is combination of 2 graphs, doesn't make sense either.
As per my understanding we wanted decaying property of e^(-x) and a graph symmetric on both side of x=0. Hence the square => e^(-(x^2)). Then scaling and shifting happened. Hence e^(-((x - mu) / sigma)^2
sending love dear sir
Sir thank you so much ❤ very much appreciated
thank u for informative sessions.. You are best
mera teacher paid course ka sir ka contant same copy krta hai. balki kar bhi nahi pata ache se. or dusra sir ki mehnat ko khood ki batata khood pta ni lgta. or kehta hai ki one of my intern ne project bnya hai. jabki wo nitish sir ke intern ne bnaya tha
best
generally Mode < Median < Mean for positive skewed distribution, but if the data values are huge near the peak then mean will shift towards left and mean may becomes < median in that case right? I checked, this happens, I just wanted to confirm from you that this understanding (Mode < Median < Mean) is not all true right for +ve skewed? It may depend on the data points.
osm sir
This channel is for all (beginners to experience) .
do you have paid vdieo asccess bro
You are gem❤
than you
Sir jab hum max range ikal rahe hai to outlier check karne k liye to apne bha pr mean nikal kar 3 std se + kiy bo ku kiya
Agar hum normally 3 std nikal le tab bhi to bo max value bata dega na + karne ka kya logic hai pls btayia
thank u
MashaAllah sir looking handsome in this haircut ❤️
verry nice
Tableu and powerbi bhi kra dijiye
Why have I not seen your videos earlier!!!
P,lease make a live session on time series
Can you please give the session 41 notebook link?
Notebook Pdf link is now added in the description
@@sumankumarsuman2656 I want to enroll in this program how can I get it .
Can the value of pdf be more than 1? If so, then how? plz answer
No. Because probability can't be greater than one.
I'm also 5 std away from the mean but on the left side
sir ap kab live atty hain mentor ship pr plz mujhy kuch doudt hain plz
@ 8 pm
@@ankushsingh8154hey I want to enroll in campusx data science program could you please help me out in that
Hi sir
Please share yesterday's pdf sir
Notebook Pdf link is now added in the description
@@sumankumarsuman2656 no bro,that was previous class notebook
@@sumankumarsuman2656 I got thank you bro
36:21
sir u ar din briadman in this field
Bradman avg:- 99.97
Next best
Steve Smith:- 58
Irrelevant to topic !
Sir Hame data Science/ ML engineering Karne ka liya
Data structure and alogorithm parna zarori ha
ha todha sa baic padna hogha ml ka liya but advance ma ni jana ml ma but most of time ml enigneer sa case study kartha ha interview ma
1:52:41 : or condition should be used 😅
virat kohli is the outlier