what is better to use?
linear regression algorithm or the models from sklearn?
I am very comfortable with using the sklearn, but in case it is not efficient or wont help in future, i can make a switch now.
What is better to use?
Hey @itzsakshi26gupta, algorithms to be used completely depends on the use case as well as the dataset you want to work with. When you know the relationship between the independent and dependent variable have a linear relationship, this algorithm is the best to use because of it’s less complexity as compared to other algorithms.
On the other hand in linear regression technique outliers can have huge effects on the regression and boundaries are linear in this technique.
In short we can say Linear Regression is a great tool to analyze the relationships among the variables but it isn’t recommended for most practical applications because it over-simplifies real-world problems by assuming a linear relationship among the variables.
I hope this resolves your doubt !
Please mark the doubt as resolved in your doubts section !
Happy Learning 
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