Lab | Supervised Learning Model Evaluation

Introduction

In the Supervised Learning Model Evaluation lesson, we learned about a variety of model evaluation metrics that we could use to measure the performance of both regression and classification models. In this lab, we will practice calculating these metrics on regression and classification data sets.

Getting Started

Open the main.ipynb file in the your-code directory. There are a bunch of questions to be solved. If you get stuck in one exercise you can skip to the next one. Read each instruction carefully and provide your answer beneath it.

Deliverables

• main.ipynb with your responses to each of the exercises.

Submission

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

Resources

• Scikit-learn Metrics Documentation
• Model evaluation: quantifying the quality of predictions