P R.E S E N T S              .

Practical Machine Learning And Image Processing

DATE: 21-03-2020  SIZE: 7.3 MB      DISKS: 1x50.00MB   PAGES: n/a

PUBLISHER: Apress                            GENRE:

AUTHOR: Himanshu Singh

FORMAT: EPUB  PROTECTION: DRM  EDITION: n/a

URL: https://is.gd/J2iwql

LANGUAGE: English   ISBN: 9781484241493

: 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 Fo :
: Data scientists and software developers interested in image processing and :
: computer vision.                                                           :

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