ta-data-par / lab-ml-supervised-sklearn

Lab | Supervised Learning with Scikit-Learn

Introduction

In this lab, we will begin to explore the scikit-learn library in the context of supervised learning.

Getting Started

Open the main.ipynb file in the your-code directory. Follow the instructions and add your code and explanations as necessary. By the end of this lab, you will have learned about the scikit-learn library and about different aspects of linear regression.

Deliverables

• main.ipynb with your responses.

Submission

Upon completion, add your deliverables to git. Then commit git and push your branch to the remote.

Resources

sklearn.datasets.load_diabetes

sklearn.linear_model.LinearRegression

StatsModels Linear Regression

StatsModels Linear Regression Ordinary Least Squares

Linear Model Hypothesis Testing

The Coefficient of Determination, r-squared

R squared in scikit-learn

Recursive Feature Elimination