Lab | Principal Component Analysis

Introduction

In this lab, we will learn about dimensionality reduction of data using principal component analysis. We will find the most important components in our data and reduce the amount of columns to enable visualization of high dimensional data.

Getting Started

Open the main.ipynb file in the your-code directory. Follow the instructions and add your code and explanations as necessary. By the end of this lab, you will have learned about dimensionality reduction using PCA.

Deliverables

• main.ipynb with your responses.

Submission

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

Resources

PCA in statsmodels

A paper about PCA in image processing

PCA in Wikipedia