Lab | Ensemble and Bias Variance

Introduction

In this lab, we are going to explore how ensembling can help us manage the bias-variance tradeoff.

Getting Started

Open the ipynb file in your-code directory. Follow the instructions and add your code and explanations as necessary. By the end of this lab, you will have learned how ensembling can be a powerful tool to reduce variance and bias significantly in your ML workflows.

Dataset from UC Irvine

Deliverables

• ipynb with your responses.

Submission

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