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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Machine Learning for OpenCV (Paperback)
Loot Price: R1,314
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Machine Learning for OpenCV (Paperback)
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Expand your OpenCV knowledge and master key concepts of machine
learning using this practical, hands-on guide. About This Book *
Load, store, edit, and visualize data using OpenCV and Python *
Grasp the fundamental concepts of classification, regression, and
clustering * Understand, perform, and experiment with machine
learning techniques using this easy-to-follow guide * Evaluate,
compare, and choose the right algorithm for any task Who This Book
Is For This book targets Python programmers who are already
familiar with OpenCV; this book will give you the tools and
understanding required to build your own machine learning systems,
tailored to practical real-world tasks. What You Will Learn *
Explore and make effective use of OpenCV's machine learning module
* Learn deep learning for computer vision with Python * Master
linear regression and regularization techniques * Classify objects
such as flower species, handwritten digits, and pedestrians *
Explore the effective use of support vector machines, boosted
decision trees, and random forests * Get acquainted with neural
networks and Deep Learning to address real-world problems *
Discover hidden structures in your data using k-means clustering *
Get to grips with data pre-processing and feature engineering In
Detail 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!
Style and approach OpenCV machine learning connects the fundamental
theoretical principles behind machine learning to their practical
applications in a way that focuses on asking and answering the
right questions. This book walks you through the key elements of
OpenCV and its powerful machine learning classes, while
demonstrating how to get to grips with a range of models.
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