I watched many videos to learn linear regression concept .. but only ur videos has taught me a clear picture . Great effort brother... Pls put more videos , eg., Decision tree and Randome forest algorithms
I have seen many videos but I couldn't understand how to train and split.. Now I got a clear picture... I owe you brother.... Thank you so much for your video to get excellent understanding.... Love you bro❤...
Thanks for the wonderful videos, bro! If possible, could you suggest a video link for the Gradient Descent algorithm? If not, could you please create a video on it? Additionally, it would be great if you could make a video on multiple linear regression, bro. Nandri!
Reason : It for interpretability of the final model . RMSE measure the average error (same units as target variable) . Example: If target variable is house price(rupees) then RMSE will give average error in rupees. That's why we say its more interpretable MSE measure the average SQUARED error ( this is not the same units as target variable since square comes into picture here). Example: If target variable is house price(rupees) then MSE will give average squared error in rupees. That's why we say its not interpretable . How to over come this ? If you apply square root on squared value then square root and square will cancel out each out thats why we use RMSE . Thanks Like Share subscribe if found helpful and check out other playlist videos in my channel.
Thanks a lot bro ...great explanation waiting for deployment video :)....pls continue to upload more videos reg ML and a request to upload why and when to use gradient descent in linear regression model
@@PythonOdyssey_ajith also bro integers ilama string objects matum irunthal how to clean data and use LR nu solikodunga de vision tree vachu than seiya mudiyuma?
I watched many videos to learn linear regression concept .. but only ur videos has taught me a clear picture . Great effort brother... Pls put more videos , eg., Decision tree and Randome forest algorithms
thanks for the feedback , sure will do it . Like Share Subscribe if found helpful
I have seen many videos but I couldn't understand how to train and split.. Now I got a clear picture... I owe you brother.... Thank you so much for your video to get excellent understanding.... Love you bro❤...
glad it helped you :)
Like Share subscribe if found helpful and check out other playlist videos in my channel
You doing out of box man ,I amazed thank you so much brother.
glad it helped you :)
Like Share subscribe if found helpful and check out other playlist videos in my channel
very usefull bro...🙌
thanks bro for the feedback ! Like Share subscribe if found helpful and check the other playlist videos !
Bro multiple regression podunga
Thanks sure will do it.
Like Share subscribe if found helpful and check out other playlist videos in my channel.
End to end machine learning project potunga na rompa useful ah irukum..Tamil la yarum potala
sure nanba
@@PythonOdyssey_ajith thank you na
Thanks for the wonderful videos, bro! If possible, could you suggest a video link for the Gradient Descent algorithm? If not, could you please create a video on it? Additionally, it would be great if you could make a video on multiple linear regression, bro.
Nandri!
sure bro will cover all topics in AI/ML will upload it soon .
Like Share subscribe if found helpful and check out other playlist videos in my channel.
brother why we can use rmse in linear regression bcz mse also predict the value
Reason : It for interpretability of the final model .
RMSE measure the average error (same units as target variable) .
Example: If target variable is house price(rupees) then RMSE will give average error in rupees. That's why we say its more interpretable
MSE measure the average SQUARED error ( this is not the same units as target variable since square comes into picture here).
Example: If target variable is house price(rupees) then MSE will give average squared error in rupees. That's why we say its not interpretable .
How to over come this ? If you apply square root on squared value then square root and square will cancel out each out thats why we use RMSE .
Thanks
Like Share subscribe if found helpful and check out other playlist videos in my channel.
Thanks a lot bro ...great explanation waiting for deployment video :)....pls continue to upload more videos reg ML and a request to upload why and when to use gradient descent in linear regression model
Nandri , sure will do it .
do we need to try it out by applying in these formula ? has anybody tried ?
Kindly elaborate your query .
Like Share subscribe if found helpful and check out other playlist videos in my channel.
Thanks a ton Sir. The letters are too small to read in the jupyter note book. Is there any way we increase the size of them to see better?
sry abt that will increase the font size in upcoming videos ! Will upload this notebook in my git repo and will share the url soon!
@@PythonOdyssey_ajith
Thank you Sir. I am a senior citizen much interested in Optimization techniques using Python.
sure sir will cover those topics soon .
@@PythonOdyssey_ajith Thank you Sir once again
Hi Sir please use below link to download the notebook and csv file used in this video github.com/AjitAntony/simple_linear_regression
Multi variable linear regression vachu coding pani katunga...I find it difficult to clean the data and extract
sure will do it
@@PythonOdyssey_ajith also bro integers ilama string objects matum irunthal how to clean data and use LR nu solikodunga de vision tree vachu than seiya mudiyuma?
@@PythonOdyssey_ajith brother personal ah sila guidance koduka mudiyuma . I am doing my projects in ML . Few doubts clarify pana mudiyuma?
string/categorical features must be onhot encoded .this will also inturn increase your no of features , will upload a use case video regarding this .
bro ennaku machine learning solli tharingala bro