Practical Machine Learning and Image Processing

For Facial Recognition, Object Detection, and Pattern Recognition Using Python

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Éditeur :

Apress


Paru le : 2019-02-26



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Description




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 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.

Pages
169 pages
Collection
n.c
Parution
2019-02-26
Marque
Apress
EAN papier
9781484241486
EAN PDF
9781484241493

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
16
Taille du fichier
4936 Ko
Prix
62,11 €
EAN EPUB
9781484241493

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
16
Taille du fichier
7475 Ko
Prix
62,11 €

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