car-linear-regression's Introduction

Plaid Coat

Description

Practice using linear regression through exercises looking at data on car sales.

Objectives

After completing this assignment, you should be able to:

Use scikit-learn to perform linear regression
Understand single-variable and multiple-variable linear regression
Decide when to use polynomial linear regression of differing degrees
Understand the use dummy variables when fitting lines with linear regression

Tasks

* [ ] Blank slate
  * [ ] Create a GitHub repo called `car-linear-regression`
  * [ ] Copy all the files from this repo into it
  * [ ] Set up your requirements/virtual environment
* [ ] Normal mode
  * [ ] Complete the tasks in the `car-worth.ipynb` file
  * [ ] Make sure your findings are well-organized, using Markdown headers and formatting to separate sections
  * [ ] Ensure your notebook runs when all the outputs are cleared and the cells are run in order (restart your kernel, clear all outputs, and run all cells)

Details

Deliverables

A Git repo called linear-regression containing at least:
- a requirements.txt file
- car-worth.ipynb
- supporting data files

Normal Mode

Go through the car-worth.ipynb file included with this repository and add cells to address the prompts, exploring the data through the use of pandas and scikit-learn.

Your final submission should be a well-organized IPython notebook file with charts and data exploring linear relationships in the data.

Recommend Projects