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.

利用Python中的机器学习和神经网络，获得对图像处理方法和算法的深入了解。本书从环境设置开始，了解基本的图像处理术语，并探索对实现书中讨论的算法有用的Python概念。然后，在进入最大的计算机视觉库之前，你将详细地介绍所有的核心图像处理算法。OpenCV。你将看到OpenCV的算法以及如何使用它们进行图像处理。

下一节着眼于图像处理和分类的高级机器学习和深度学习方法。你将使用脉冲耦合神经网络、AdaBoost、XG boost和卷积神经网络等概念来进行图像的具体应用。之后你将探索如何实时制作模型，然后使用各种DevOps工具进行部署。

实用机器学习和图像处理》中的所有概念都是用实际生活中的场景来解释的。阅读本书后，你将能够应用图像处理技术，并为定制的应用制作机器学习模型。

你将学到什么

使用Python发现图像处理算法和它们的应用

探索使用OpenCV库的图像处理

使用TensorFlow、scikit-learn、NumPy和其他库

使用机器学习和深度学习算法进行图像处理

在五个实时项目中应用图像处理技术

本书适用对象

对图像处理和计算机视觉感兴趣的数据科学家和软件开发人员。