num_pages: 382
description: Expand your OpenCV knowledge and understand key machine learning concepts using this practical guide Machine learning is no longer just a buzzword it is all around us - right from protecting your email and automatically tagging friends in pictures through to predicting the movies you like. Computer vision is one of the most exciting fields for machine learning application with deep learning driving innovative systems such as self-driving cars and Google's DeepMind. OpenCV is significantly related to 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 get easy access to a wide range of open source computing libraries. This book begins by introducing you to the essential concepts of statistical learning such as classification and regression. Once you have learned the basics you will explore a variety of algorithms such as decision trees support vector machines and Bayesian networks and learn how to combine them with other OpenCV functionalities. As you progress you'll build on your machine learning skills and explore one of its most important concepts - deep learning. You'll even be able to use it for classifying handwritten digits. Finally the book will summarize everything you've learned and help you tackle machine learning problems using the tools covered in the chapters. By the end of this book you will have the skills you need to address different machine learning challenges either by building on the existing source code or developing your own algorithm from scratch. This book is for Python programmers who are already familiar with OpenCV.
language: English
title: Machine Learning for OpenCV: Intelligent image processing with Python
publisher: Packt Publishing