Let's start with linear regression, the most commonly used supervised machine learning algorithm. In this module, you'll learn how to:
Fit a line to data
Measure loss with residuals and sum of squares
Use scikit-learn to fit a linear regression
Evaluate a linear regression using R2 and train-test splits
For this exercise, open a new Jupyter Notebook to practice in a new browser window. Or, if you'd like to work directly within the exercise notebook, you can download it below. After this lesson, we'll test your knowledge with a quiz.
oldoc63
commented
1 year ago
Let's start with linear regression, the most commonly used supervised machine learning algorithm. In this module, you'll learn how to:
For this exercise, open a new Jupyter Notebook to practice in a new browser window. Or, if you'd like to work directly within the exercise notebook, you can download it below. After this lesson, we'll test your knowledge with a quiz.
Residuals