Book Image

Machine Learning for OpenCV

By : Michael Beyeler
Book Image

Machine Learning for OpenCV

By: Michael Beyeler

Overview of this book

Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google’s DeepMind. OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for. Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch!
Table of Contents (13 chapters)

Approaching a machine learning problem

When you see a new machine learning problem in the wild, you might be tempted to jump ahead and throw your favorite algorithm at the problem--perhaps the one you understood best or had the most fun implementing. But knowing beforehand which algorithm will perform best on your specific problem is not often possible.

Instead, you need to take a step back and look at the big picture. Before you get in too deep, you will want to make sure to define the actual problem you are trying to solve. For example, do you already have a specific goal in mind, or are you just looking to do some exploratory analysis and find something interesting in the data? Often, you will start with a general goal, such as detecting spam email messages, making movie recommendations, or automatically tagging your friends in pictures uploaded to a social media platform....