Sir your videos deserve lot more views than it has. Best content found ever !!
@siyays1868
2 жыл бұрын
Ur videos really clears everyone's doubt. Hatts off to ur dedication.
@ParthivShah
7 ай бұрын
Thank You Sir.
@rockykumarverma980
15 күн бұрын
Thank you so much sir🙏🙏🙏
@sowmyak3326
Жыл бұрын
Hi sir, thanks a lot for your videos. I really learnt a lot. But, I have a small question should we consider the scale of independent variables? Wouldn't scale have an impact on coefficients?
@abhishekkukreja6735
2 жыл бұрын
Hi nitish sir, at 10:57 you said all the less impacted coefficients will be 0 but you said in ridge regression that when lambda is increased it impacts the highly impacted coefficients which then tends to infinity and so how in lasso we are able to decrease the less impacted coefficients , while increasing the lambda ???? will be looking for your reply nitish sir.
@ajaykushwaha-je6mw
3 жыл бұрын
Awesome video, sir ek request hai. Please ek video banaiye for Hypertuning L1 and L2 k liye so that hum best choose ker payein for both.
@campusx-official
3 жыл бұрын
Okay. Noted
@sidindian1982
2 жыл бұрын
@@campusx-official Sir Code : Understanding of Lasso Regression Key points. not able to download ..pls help
@ujjalroy1442
Ай бұрын
Awesome sir...
@anirbanmukherjee8574
Жыл бұрын
As per SVM discussion, lambda is inversely proportional to alpha value. So, lambda increases bias should be low as it will lead to overfitting? Please let me know, if my understanding is right or wrong?
@gamesden8021
Жыл бұрын
sir your videos is so interesting but my question is circle and loss function contor plot pr hamara solution mil raha hai ridge regression sy jabky woh point error hoga because woh point tu local minima yeah global minima nahi hai
@gamesden8021
Жыл бұрын
sir my question is ky apny previous video ma kaha tha m higher hai tu woh fastly decrese kary ga jabky is ma apny kaha ju less important columns hain it think jis ka m small hai woh fastly equal to zero ho jahain gai plz solve my douts
@KN-tx7sd
2 жыл бұрын
Sir, thank you. You have described the effect of different values of Lamba on the feature selection. However, for a study with n number of features how do we know which lambda is the best no overfitting or no underfitting? Is there a standard formula/script that could be used to identify this value for lambda for any study?
@manishnayak9759
Жыл бұрын
by cross validation technique you will get the best lamda
@GamerBoy-ii4jc
2 жыл бұрын
Sir please make any telegram or whatsapp group for Student discussion. Thanks!
@parthshukla1025
3 жыл бұрын
Thanks A Lot Sir !!!
@yuktashinde3636
Жыл бұрын
THANK YOU GURU
@near_.
Жыл бұрын
Are you doing any project
@rohitdahiya6697
Жыл бұрын
why there is no learning rate hyperparameter in scikit-learn lasso/Elasticnet . As it has a hyperparameter called max_iteration that means it uses gradient descent but still there is no learning rate present in hyperparameters . if anyone knows please help me out with it.
@uditjec8587
11 ай бұрын
@25:31 r2 score is negative. but r2 score can not be negative. Then how r2 score is negative here?
@SPARSHKUMAR-f4h
6 ай бұрын
I have 1 confusion, ||W||^2 would be lambda * (W0^2 + W1^2 -----) right not lambda * (W1^2 + W2^2)
@suvithshetty2350
4 ай бұрын
consider only the slope as W0 is intercept you don't have to consider it.
@abhirupmukherjee6405
9 күн бұрын
Its summation i=1 to n Lambda Wi²
@coding_world_live9
2 жыл бұрын
Thanku sir
@RahulRathour-v3d
10 күн бұрын
why it's called lasso regression?
@RohanOxob
Жыл бұрын
13:05
@divyanshchaudhary7063
3 ай бұрын
Sir notes thode dhang se bna liya karo paid subs bhi le rakha hai pata nahi konsi chiz kha jaa rhi hai revesion ke time.
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