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A brief description of the article -

There are innumerable form of regression techniques which can be performed and this article includes 7 major regression techniques every data scientist should know. The article briefly discusses the concept behind each algorithm and explains what are the conditions to consider while deciding which algorithm should be implemented.

Why we use Ridge and Lasso regression and what is multicollinearity?Can anyone explain in simple words

Hi @nitika30

Multicollinearity is when the independent variables are highly correlated. For example, birth year and age columns. Considering both the columns for your prediction is not appropriate. In this case, you can use ridge and lasso regression.

The following article covers Ridge and Lasso regression in detail.

1 Like

Really a Awesome article for understanding the regression models, But some few regressions are left out. Beta regression, probit regression, tobit regression, multinomial logistical regression and probably a few others. Overall the article was so good you nailed it. Thanks for sharig one of the greatest and Informative article.

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