Linear Regression with OLS: Simple & Multiple Regression

1. 1Run a simple linear regression using OLS to understand the relationship between two variables
2. 2Apply multiple linear regression using OLS to model the relationship between multiple independent variables and a dependent variable
3. 3Configure a linear regression model using a library like scikit-learn to implement OLS
4. 4Test the model using metrics like mean squared error and R-squared to evaluate its performance
5. 5Compare the results of simple and multiple linear regression to determine the best approach for a given problem

Data scientists and analysts can benefit from this article to improve their regression analysis skills, while machine learning engineers can apply these concepts to build predictive models

💡 Ordinary Least Squares (OLS) is a fundamental method for simple and multiple linear regression, allowing for the estimation of relationships between variables

Boost your data science skills with linear regression using OLS!