Hindi- Overfitting, Underfitting,Bias And Variance Explained In Hindi| Machine Learning

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OMG!!! Was it that easy? I found this very difficult before watching your video. thnk u so much ....

[@sagaragalawe1536]

Many videos I have seen on TH-cam. But your teaching is much understandable than others.

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Wow..thanks a lot sir ,please continue this series.

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hum but the price is 😥

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[@djsatgeet6006]

Sir, for this kind of content. Beautifully Explained

[@gupta_festvloger1894]

Truely no words to thanks mind-blowing, great ❤❤❤

[@pankhurithakur4291]

very nice, bhot acha padhaya sir ne tysm

[@user-mh3qd4su3j]

Krish sir, Thank you very much for making this video. Love you sir. you are among the top great teachers of DS
.

[@Nandanyadav333]

Nice explanation bro thank you❤

[@letsrockwithnavin11]

Model 1- Overfitting
Model 2- Underfitting
Model 3- General fitting,,,
THANKS SIR, FOR MAKING THIS PLAYLIST, hm ek institute se DATA SCIENCE ka course ker rhe hai (total charge 1.8 L), but hmko wha se utna samjh me nhi aaya hai jitna ki aapke video dekh ker samjh me aa rha hai... Thanks Sir

[@shobhangiverma7090]

Thankyou for wonderful video sir🙏

[@adilmughal2251]

explained beautifully.

[@keeratkaur7012]

Explained very well😁

[@pythonthepythonist6439]

Addicted to all your videos, can't stop watching, I keep repeating all your videos, I can't my self believe that I am knowledgeable... iam not fan of any movie heros....but huge fan of you 👏

[@PritamSarkar-fe8ye]

Was finding this. ♥

[@cha5848]

Thanku so much

[@aryanjaiswal9829]

nice video sir

[@SACHINKUMAR-px8kq]

thanks sir

[@agrawalmitesh4395]

Masterpiece

[@vivekpaliwal1876]

sir linear regression me jo best fit line to straight line bnti hai ... y = mx + b....to ye tedi line best fit kese ho skti hai?

[@UNKNOWNSAAKASH-so2ou]

First model is Low Bias + High Varience (Overfitting)
Second model is High Bias + High Variance also (underfitting)
Third model is Low Bias + Low Varaince. (Generalized)

[@priyansukushwaha5195]

you made ml easy to love

[@user-pe4lw2ff7o]

Excercise 9:55 / 12:17
Model 1-> Low Bias, High Variance (Overfitting)
Model 2-> High Bias, High Variance(Underfitting)
Model 3 -> Low Bias , Low Variance (Generalized Model)

[@shahrukhahmad4127]

Timestamp:9:55 >>>> Model1: Overfitting, Model2: Underfitting, Model3: Generalized model

[@AbdullahAbdullah-jc4uf]

👍

[@samarthtandale9121]

Sir muze samaz nahi araha hai ki linear regression me ovrfitting kaise ho sakta hai ... after all it is a line!

[@bhupeshmahara]

Sor, what if in regression model in the 3rd graph, if we have training error almost 0 and variance is also low ??

[@krishnaikhindi]

It is a generalized model

[@bhupeshmahara]

@@krishnaikhindi thanks sir

[@kokandarshan4173]

👌👌❤️🙏🙏🙏🙏

[@PiyushKumar-ps5yu]

10:44 wrong underfitting (high bias + low variance)

[@propagandabuster9280]

Why low variance bro?? Test data error is high na so high variance..

[@pratiksingh23]

11:42

[@mlpython1089]

What language is he speaking?

[@aniketsrivastava6521]

Hindi