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: Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python
: Himanshu Singh
: Apress
: 2019
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: pdf (true), epub
: 12.5 MB

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. Youll 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. Youll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later youll 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.

Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python












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