Lasso Regression with Scikit-Learn (Beginner Friendly)

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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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As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I've transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I've discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.

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  1. Ryan & Matt Data Science
  2. Data Analyst
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Комментарии
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Hey guys I hope you enjoyed the video! If you did please subscribe to the channel!


*Both Datacamp and Stratascratch are affiliate links.

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

RyanAndMattDataScience
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Just found your channel, loving the python tutorials

ryuhayabusa
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so what if the lasso drop two features who can you tell which features it dropeed when you zip teh freatures and coeef back together???

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

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

lockelancer
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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 :)