So, you have decided to enter the field of machine learning. That's great!

Nowadays, machine learning is all around us—from protecting our email, to automatically tagging our friends in pictures, to predicting what movies we like. As a form of artificial intelligence, machine learning enables computers to learn through experience; to make predictions about the future using collected data from the past. On top of that, computer vision is one of today's most exciting application fields of machine learning, with deep learning and convolutional neural networks driving innovative systems such as self-driving cars and Google's DeepMind.

However, fret not; your application does not need to be as large-scale or world-changing as the previous examples in order to benefit from machine learning. In this chapter, we will talk about why machine learning has become so popular and discuss the kinds of problems that it can solve. We will then introduce the tools that we need in order to solve machine learning problems using OpenCV. Throughout the book, I will assume that you already have a basic knowledge of OpenCV and Python, but that there is always room to learn more. We will also go over how you can install OpenCV on your local system so that you can try out the code on your own.

Are you ready then? In this chapter, we will go over the following concepts:

• What is machine learning and what are its categories?
• Important Python concepts
• Getting started with OpenCV
• Installing Python and the required modules on the local system
• Applications of machine learning
• What's new in OpenCV 4.0?