Yelp was founded in 2004 to help people find great local businesses. We have partnered with Yelp Data Science team for the Linear Regression Cumulative Project and you will be working with real data from Yelp to predict the Yelp rating of a restaurant. **Note:** This project is optional; if you’re busy this week, you can skip it! To complete this project, you will be working in a Jupyter Notebook. Follow these instructions to set up your project: #### Getting Started with Jupyter Notebooks 1. If you’ve never used the command line, we recommend taking the Learn the Command Line course. 2. Install Python by following the directions in this article on Installing Python for Data Analysis. 3. Learn about Jupyter Notebooks, a cool way of combining Python code with explanations or instruction in a web terminal. 4. Read the Yelp Dataset Terms of Use (on the next page). 5. Accept the Terms of Use (on the bottom) to download the Yelp project. 6. Unzip it by double-clicking on it. 7. In the terminal, navigate to the directory containing the project, and type: ``` jupyter notebook ``` This should open a browser tab. 8. The project can be found in **yelp_regression.ipynb**. Click on the file to begin. 9. Follow the steps in the Jupyter Notebook. If you get stuck, you can look at the solution found in **yelp_regression_solution.ipynb**. --- Thank you Yelp for this partnership and especially: - **Sebastian Couvidat**, Sr. Data Scientist - **Jenny Lin**, Data Scientist - **Jessica Hart**, Corporate Counsel

Happy Coding!