# Introduction

I am willing to bet that if you walk by any group of computer scientists, you will hear "machine learning" or "ML" at least once. By the end of this tutorial, you will know what it is, and be qualified enough to put "machine learning expert" on your resume. (Ok, maybe not quite.) The reason that ML is so popular is that, if used properly, it is a powerful way to analyze the world around us.

**Disclaimer:** Machine learning involves a significant amount of math. This tutorial will not assume that you have a heavy math background but as you dive in on your own, this is something to consider. Some areas that are especially relevant to ML include:

- Calculus
- Probability
- Statistics
- Linear Algebra