July 2017
Intermediate to advanced
382 pages
9h 13m
English
Overview
Delve into the powerful combination of OpenCV and Python with this hands-on guide to machine learning and image processing. From foundational principles to implementing real-world image analysis systems, this book provides an accessible and in-depth exploration of modern techniques like deep learning.
What this Book will help me do
- Create and leverage machine learning models for image data in Python with OpenCV.
- Master data preprocessing and feature engineering for enhanced model performance.
- Gain proficiency with popular algorithmic approaches like SVMs, Bayesian classifiers, and decision trees.
- Dive into deep learning frameworks to build cutting-edge computer vision applications.
- Understand efficient model evaluation and selection methods to optimize predictive systems.
Author(s)
Michael Beyeler is a recognized expert in computer vision and machine learning, combining academic insights with real-world applications. With years of experience in using OpenCV and Python, he crafts clear and engaging tutorials for budding data scientists and professionals. His contributions are widely appreciated for demystifying complex concepts.
Who is it for?
This book is ideal for Python developers who are familiar with programming and have a basic understanding of OpenCV. It is tailored for readers eager to master machine learning concepts and develop practical image processing applications. If you wish to apply powerful algorithms to solve vision tasks efficiently, this book is for you.
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