Lasso Regression with Scikit-Learn (Beginner Friendly)

Welcome to our comprehensive tutorial on Lasso Regression using the scikit-learn library in Python! In this video, we dive deep into the world of Lasso Regression, a powerful machine learning technique used for feature selection and regularization.
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[@RyanAndMattDataScience]

Hey guys I hope you enjoyed the video! If you did please subscribe to the channel! If you want to watch a full course on Machine Learning check out Datacamp: datacamp.pxf.io/XYD7Qg Want to solve Python data interview questions: stratascratch.com/?via=ryan I'm also open to freelance data projects. Hit me up at [e-mail] *Both Datacamp and Stratascratch are affiliate links.

[@ryuhayabusa3540]

Just found your channel, loving the python tutorials

[@RyanAndMattDataScience]

Glad you like them! I put out about 3 a week

[@HenriqueSantos-xd1eg]

have you tried pycaret?

[@RyanAndMattDataScience]

I made a mistake within this video: fit_transform must be only on train set, for test there must be only transform.

[@736939]

Dear Ryan, could you please write all these codes with pipelines and columns transformers, it would be great to see the best practice with all sklearn pipeline tools. Thank you for this great work, and more feature engineering please :)

[@RyanAndMattDataScience]

Hey, have a pipeline and transformer videos. + working on a Kaggle project with them. I’ll also be using pipelines with the voting regressor + stacking vids. For the simple model vids, going to focus on background of model, basic example, and tuning

[@lockelancer8193]

Very useful video, very cool. Saved me a bunch of time and effort from trying to learn it R A W.

[@RyanAndMattDataScience]

Awesome glad you found some value

[@misterx3321]

Nice video! Say does LASO-Regression only apply to multiple linear regression where you have multiple variables that contribute to the target variable?

[@RyanAndMattDataScience]

no, it can be applied to other linear regressions although multiple is probably most common