Polynomial Regression with Scikit-Learn

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In this lecture, we will delve into the world of polynomial regression and explore how to use polynomial features in linear regression models. We will begin by discussing what polynomial regression is and how it differs from linear regression. Then, we will dive into the concept of polynomial features and how they can be used to create polynomial regression models.

We will also demonstrate how to implement polynomial regression using Scikit-Learn, a popular Python library for machine learning. We will walk through an example to illustrate how to create polynomial features, fit a polynomial regression model, and make predictions.

By the end of this lecture, you will have a deep understanding of polynomial regression and how to use polynomial features in linear regression models. You will also have the skills to implement polynomial regression models using Scikit-Learn in your own machine-learning projects.

github: https://github.com/AhmadDawood225/Data-Science/tree/main/Data%20Science/Module-2%20Supervised%20Learning%20Regression/12--Polynomial%20Regression

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