Stock Market Clustering-Data Science Projects

In this project, we will be extracting live Stock Market data from yahoo finance. We will find similarities amongst various companies using their stock market prices and then cluster them into different clusters using the K-means algorithm.

Note that is an unsupervised machine learning problem and will use an unsupervised machine learning technique with the help of the K-means algorithm.

NB: “pandas_datareader” extract data from various Internet sources into a DataFrame. Currently, the following sources are supported:

Yahoo! Finance

Google Finance

St.Louis FED (FRED)

Kenneth French’s data library

World Bank

Google Analytics

….and few others

Before we start, please note that this tutorial is part of the The Full Stack Data Scientist Bootcamp, which is a practical hands-on data science tutorial for anyone to learn data science right from the basics to advance by building projects and great Data Science Portfolio. Feel free to check it out.

In order for you to make the best out of this tutorial, I have put this tutorial in the form of a video for better understanding

Watch and work along

INTRODUCTION

PART 1

PART 3

GOOD LUCK

If you are interested in learning Data Science, the right way, I advise you to start with this course that focuses on teaching and building end-to-end data science projects.

I will also be posting more FREE Data Science Projects on the Youtube Channel, so don’t forget to subscribe and hit the notification bell to get notified anytime I post them.

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