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Multiple Linear Regression using python ( Regression Analysis ) 

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​‪@MLwithme1617‬ Multi Linear Regression with python | Machine Learning Lectures | what is feature engineering? how to do feature selection ?
Topics covered:
TIMESTAMPS
01:45 Data Collection
02:17 Exploratory Data Analysis (EDA)
06:40 Distribution of data
08:27 Feature Engineering
10:20 Feature selection
03:59 Model Building and evaluation
data : www.kaggle.com...
code : github.com/mle...
Twitter: / mlwithme1617
Instagram: ...
Install python : www.python.org/
Intall Jupyter Notebooks: jupyter.org/in...
Learn Python Basics : www.w3schools....
statistics, regression, probability, t statistics,z scores
#machinelearning #datascience #linearregression #simplelinearregression #multilinearregression #python #pythonprogramming #MSE #meansquarederror #sklearn #pandas #regression #regressionanalysis #chatgpt #basics #beginner

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8 сен 2024

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Комментарии : 8   
@ahcai8578
@ahcai8578 Год назад
Hi Sir, for the region can we use get_dummies instead of the ordinal way(0,1,2,3)? Thank you.
@MLwithme1617
@MLwithme1617 Год назад
Region is actually considered as nominal because regions don’t really have any ranks. But using get dummies we have chances to end-up with multicollinearity. Instead i converted them to 0,1,2,3. You can try using dummies and check the correlation matrix to see if there is any multicollinearity.
@ahcai8578
@ahcai8578 Год назад
@@MLwithme1617 thanks Sir, I will try it. Thanks for the video, it is great!
@bharadwajkamepalli3903
@bharadwajkamepalli3903 Год назад
@@MLwithme1617 I think we can use dummies method and remove any one column that will work right?
@hmatinnn
@hmatinnn 2 месяца назад
👍
@JjayFabor
@JjayFabor Год назад
Hi Sir, can you do a video tutorial on how can you improve the r2 score? Thank you
@amirman6531
@amirman6531 5 месяцев назад
How do we calculate Mean Square Error (MSE) for this. after all the calculation?
@MLwithme1617
@MLwithme1617 5 месяцев назад
Use MSE from sklearn, or for better understanding the math you can have a look at my explanation video on MSE.
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