sideround / lab-regression-analysis

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Lab | Regression Analysis

Introduction

Regression analysis is one of the most fundamental and powerful algorithms used in data analytics and data science. In this lab, we are going to apply what we have learned about different types of regressions, and use them to understand the trends in our data, and predict future values of our outcome.

Getting Started

Go to the folder lab-regression-analysis in the GitHub repo. Open the file lab-regression-analysis.ipynb in the your-code directory. Read the question carefully and provide thoughtful solutions in the space provided. The datasets to be used in the exercises has been provided on GitHub here.

Happy Learning!

Expectations

  • Write clean, well-commented code
  • Fully explain your responses where necessary
  • Refer to the lecture notes if you have questions
  • Don't be afraid to ask your TAs for help!

Deliverables

  • 'your-code.ipynb' with your responses

Submission

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

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