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Practical Machine Learning and Image Processing - For Facial Recognition, Object Detection, and Pattern Recognition Using Python (Paperback, 1st ed.)
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Practical Machine Learning and Image Processing - For Facial Recognition, Object Detection, and Pattern Recognition Using Python (Paperback, 1st ed.)
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Gain insights into image-processing methodologies and algorithms,
using machine learning and neural networks in Python. This book
begins with the environment setup, understanding basic
image-processing terminology, and exploring Python concepts that
will be useful for implementing the algorithms discussed in the
book. You will then cover all the core image processing algorithms
in detail before moving onto the biggest computer vision library:
OpenCV. You'll see the OpenCV algorithms and how to use them for
image processing. 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 concepts in 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.
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