01. Overview

Project Highlights

This project is designed to get you acquainted with the many supervised learning algorithms available in sklearn, and to also provide for a method of evaluating just how each model works and performs on a certain type of data. It is important in machine learning to understand exactly when and where a certain algorithm should be used, and when one should be avoided.

Things you will learn by completing this project:

• How to identify when preprocessing is needed, and how to apply it.
• How to establish a benchmark for a solution to the problem.
• What each of several supervised learning algorithms accomplishes given a specific dataset.
• How to investigate whether a candidate solution model is adequate for the problem.