![]() You can import pandas with the following statement: It is convention to import pandas under the alias pd. The first library that we need to import is pandas, which is a portmanteau of “panel data” and is the most popular Python library for working with tabular data. The Libraries We Will Use in This Tutorial Before we build the model, we’ll first need to import the required libraries. More specifically, we will be working with a data set of housing data and attempting to predict housing prices. ![]() This will allow you to focus on learning the machine learning concepts and avoid spending unnecessary time on cleaning or manipulating data. Since we're just starting to learn about linear regression in machine learning, we will work with artificially-created datasets in this tutorial. Section 1: Linear Regression The Data Set We Will Use in This Tutorial This tutorial will teach you how to create, train, and test your first linear regression machine learning model in Python using the scikit-learn library. In the last article, you learned about the history and theory behind a linear regression machine learning algorithm. Linear regression and logistic regression are two of the most popular machine learning models today.
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