Zabbix 5 IT Infrastructure Monitoring Cookbook. Explore the new features of Zabbix 5 for designing, building, and maintaining your Zabbix setup

Nathan Liefting, Brian van Baekel

Zabbix offers useful insights into your infrastructure performance and issues and enables you to enhance your monitoring setup with its variety of powerful features. This book covers hands-on, easy-to-follow recipes for using Zabbix 5 for effectively monitoring the performance of devices and applications over networks.The book starts by guiding you through the installation of Zabbix and using the Zabbix frontend. You'll then work your way through the most prominent features of Zabbix and make the right design choices for building a scalable and easily manageable environment. The book contains recipes for building items and triggers for different types of monitoring, building templates, and using Zabbix proxies. As you advance, you’ll learn how to use the Zabbix API for customization and manage your Zabbix server and database efficiently. Finally, you'll find quick solutions to the common and not-so-common problems that you may encounter in your everyday Zabbix monitoring work.By the end of this Zabbix book, you’ll have learned how to use Zabbix for all your monitoring needs and be able to build a solid Zabbix setup by leveraging its key functionalities.

AI and Business Rule Engines for Excel Power Users. Capture and scale your business knowledge into the cloud – with Microsoft 365, Decision Models, and AI tools from IBM and Red Hat

Paul Browne, Alex Porcelli

Microsoft Excel is widely adopted across diverse industries, but Excel Power Users often encounter limitations such as complex formulas, obscure business knowledge, and errors from using outdated sheets. They need a better enterprise-level solution, and this book introduces Business rules combined with the power of AI to tackle the limitations of Excel.This guide will give you a roadmap to link KIE (an industry-standard open-source application) to Microsoft’s business process automation tools, such as Power Automate, Power Query, Office Script, Forms, VBA, Script Lab, and GitHub. You’ll dive into the graphical Decision Modeling standard including decision tables, FEEL expressions, and advanced business rule editing and testing.By the end of the book, you’ll be able to share your business knowledge as graphical models, deploy and execute these models in the cloud (with Azure and OpenShift), link them back to Excel, and then execute them as an end-to-end solution removing human intervention. You’ll be equipped to solve your Excel queries and start using the next generation of Microsoft Office tools.

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