Learning OpenCV 3 Application Development

Samyak Datta

Computer vision and machine learning concepts are frequently used in practical computer vision based projects. If you’re a novice, this book provides the steps to build and deploy an end-to-end application in the domain of computer vision using OpenCV/C++. At the outset, we explain how to install OpenCV and demonstrate how to run some simple programs. You will start with images (the building blocks of image processing applications), and see how they are stored and processed by OpenCV. You’ll get comfortable with OpenCV-specific jargon (Mat Point, Scalar, and more), and get to know how to traverse images and perform basic pixel-wise operations. Building upon this, we introduce slightly more advanced image processing concepts such as filtering, thresholding, and edge detection. In the latter parts, the book touches upon more complex and ubiquitous concepts such as face detection (using Haar cascade classifiers), interest point detection algorithms, and feature descriptors. You will now begin to appreciate the true power of the library in how it reduces mathematically non-trivial algorithms to a single line of code!The concluding sections touch upon OpenCV’s Machine Learning module. You will witness not only how OpenCV helps you pre-process and extract features from images that are relevant to the problems you are trying to solve, but also how to use Machine Learning algorithms that work on these features to make intelligent predictions from visual data!

Hands-On Machine Learning with TensorFlow.js. A guide to building ML applications integrated with web technology using the TensorFlow.js library

Kai Sasaki

TensorFlow.js is a framework that enables you to create performant machine learning (ML) applications that run smoothly in a web browser. With this book, you will learn how to use TensorFlow.js to implement various ML models through an example-based approach.Starting with the basics, you'll understand how ML models can be built on the web. Moving on, you will get to grips with the TensorFlow.js ecosystem to develop applications more efficiently. The book will then guide you through implementing ML techniques and algorithms such as regression, clustering, fast Fourier transform (FFT), and dimensionality reduction. You will later cover the Bellman equation to solve Markov decision process (MDP) problems and understand how it is related to reinforcement learning. Finally, you will explore techniques for deploying ML-based web applications and training models with TensorFlow Core. Throughout this ML book, you'll discover useful tips and tricks that will build on your knowledge.By the end of this book, you will be equipped with the skills you need to create your own web-based ML applications and fine-tune models to achieve high performance.

OpenShift Multi-Cluster Management Handbook. Go from architecture to pipelines using GitOps

Giovanni Fontana, Rafael Pecora, Marcos Amorim

For IT professionals working with Red Hat OpenShift Container Platform, the key to maximizing efficiency is understanding the powerful and resilient options to maintain the software development platform with minimal effort. OpenShift Multi-Cluster Management Handbook is a deep dive into the technology, containing knowledge essential for anyone who wants to work with OpenShift.This book starts by covering the architectural concepts and definitions necessary for deploying OpenShift clusters. It then takes you through designing Red Hat OpenShift for hybrid and multi-cloud infrastructure, showing you different approaches for multiple environments (from on-premises to cloud providers). As you advance, you’ll learn container security strategies to protect pipelines, data, and infrastructure on each layer. You’ll also discover tips for critical decision making once you understand the importance of designing a comprehensive project considering all aspects of an architecture that will allow the solution to scale as your application requires.By the end of this OpenShift book, you’ll know how to design a comprehensive Red Hat OpenShift cluster architecture, deploy it, and effectively manage your enterprise-grade clusters and other critical components using tools in OpenShift Plus.

Learning iPhone Game Development with Cocos2D 3.0. Harness the power of Cocos2D to create your own stunning and engaging games for iOS

Kirill Muzykov

Hands-On Mathematics for Deep Learning. Build a solid mathematical foundation for training efficient deep neural networks

Jay Dawani

Most programmers and data scientists struggle with mathematics, having either overlooked or forgotten core mathematical concepts. This book uses Python libraries to help you understand the math required to build deep learning (DL) models.You'll begin by learning about core mathematical and modern computational techniques used to design and implement DL algorithms. This book will cover essential topics, such as linear algebra, eigenvalues and eigenvectors, the singular value decomposition concept, and gradient algorithms, to help you understand how to train deep neural networks. Later chapters focus on important neural networks, such as the linear neural network and multilayer perceptrons, with a primary focus on helping you learn how each model works. As you advance, you will delve into the math used for regularization, multi-layered DL, forward propagation, optimization, and backpropagation techniques to understand what it takes to build full-fledged DL models. Finally, you’ll explore CNN, recurrent neural network (RNN), and GAN models and their application.By the end of this book, you'll have built a strong foundation in neural networks and DL mathematical concepts, which will help you to confidently research and build custom models in DL.

Inkscape 0.48 Essentials for Web Designers: LITE

Bethany Hiitola

Lumion 3D Best Practices. Explore the best practices to build architectural visualizations efficiently in Lumion 3D

John Brown, Ciro Cardoso, Ciro Cardoso

Oracle Siebel CRM 8 Installation and Management. Install, configure, and manage a robust Customer Relationship Management system using Siebel CRM

Alexander Hansal

Oracle’s Siebel CRM is market-leading Customer Relationship Management software. Unmatched in functionality and scalability, Siebel enhances a company’s sales performance, improves customer satisfaction, and provides a robust Customer Relationship Management system for an organization.This practical book offers a comprehensive understanding of Siebel CRM. It is your safe vessel for navigating the deep waters of Siebel installation and system management.This book is a complete exercise in installing and managing Oracle’s Siebel CRM for your organization. You will understand the Siebel architecture and install it piece by piece. In easy-to-follow chapters, the book will guide you through the installation of Siebel server, client and third-party reporting software on Microsoft Windows and Linux, covering everything from the planning the process and software download to the installation and configuration tasks.After reading this book, you will feel fully prepared for setting up multiple servers and multi-lingual configurations. This book fosters your general understanding of the intricate features and functionality of Oracle Siebel CRM. In addition, you will learn how to support development environments and how to migrate configuration changes between environments using Application Deployment Manager.Another benefit of this book is that it teaches administrators how to establish system monitoring strategies to identify and avoid performance bottlenecks. When you have finished the book, you will feel prepared to install and manage Oracle’s Siebel CRM in a real-world environment. In addition, you will know some tricks that even seasoned experts will envy.