From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced

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Extracting and creating a DataFrame of coefficients

Extracting and creating a DataFrame of coefficients - SQL Tutorial

From the course: Complete Guide to AI and Data Science for SQL Developers: From Beginner to Advanced

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Extracting and creating a DataFrame of coefficients

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- [Narrator] Welcome back. It's home stretch time. In the last step, step 20, you applied cross validation and evaluated your model's performance. Now, let's continue the journey by extracting and creating a data frame or table of coefficients. Before we explore the model's coefficients, let's understand why this step is crucial. Now, imagine you had a recipe, but it's a secret one. In this context, your model is like a secret recipe for predicting home values. You've combined various ingredients or features to make this recipe. Each ingredient has a unique impact on the final dish, in your case, the predicted home value. So what's in this secret recipe? Well, it's the coefficients. These coefficients tell you how influential each feature is in determining home values. In the world of linear regression, coefficients are like the building blocks of your model. Each feature, like crime rate, river boundary, air quality,…

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