Overview
- Covers advanced machine learning and deep learning methods for image processing and classification
- Explains concepts using real-time use cases such as facial recognition, object detection, self-driving cars, and pattern recognition
- Includes applications of machine learning and neural networks on processed images
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Table of contents (6 chapters)
Keywords
About this book
The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools.
All the conceptsin Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application.
What You Will Learn
- Discover image-processing algorithms and their applications using Python
- Explore image processing using the OpenCV library
- Use TensorFlow, scikit-learn, NumPy, and other libraries
- Work with machine learning and deep learning algorithms for image processing
- Apply image-processing techniques to five real-time projects
Who This Book Is For
Data scientists and software developers interested in image processing and computer vision.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Practical Machine Learning and Image Processing
Book Subtitle: For Facial Recognition, Object Detection, and Pattern Recognition Using Python
Authors: Himanshu Singh
DOI: https://doi.org/10.1007/978-1-4842-4149-3
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Himanshu Singh 2019
Softcover ISBN: 978-1-4842-4148-6Published: 27 February 2019
eBook ISBN: 978-1-4842-4149-3Published: 26 February 2019
Edition Number: 1
Number of Pages: XV, 169
Number of Illustrations: 77 b/w illustrations, 14 illustrations in colour
Topics: Artificial Intelligence, Programming Languages, Compilers, Interpreters, Open Source, Python