Building Real-World Web Applications with Vue.js 3. Build a portfolio of Vue.js and TypeScript web applications to advance your career in web development

Joran Quinten

In the ever-evolving web development landscape, Vue.js stands out with its intuitive design and progressive framework, empowering developers to create interactive and dynamic web applications. This book will help you stay in the forefront of modern web technologies by mastering Vue.js through hands-on projects and practical applications.Building Real-World Web Applications with Vue.js 3 is your guide to exploring the core concepts of Vue.js, setting up your development environment, and creating your first Vue.js application. You’ll progress by building a recipe app using Vuetify, followed by leveraging data visualization to create a fitness tracker featuring dynamic dashboards using external databases and Vue-ChartJS. You'll then get to grips with multiplatform development with Quasar to deploy your app.As you develop an interactive quiz app, you’ll be introduced to server-side logic with Nuxt.js, WebSockets for real-time communication, and client-server differentiation. Additionally, you’ll study experimental object recognition using TensorFlow, leveraging machine learning and camera input, and conclude by creating a portfolio website with Nuxt and Storyblok.By the end of this book, you'll have the knowledge and confidence to create your own Vue.js applications and build a portfolio to showcase your Vue.js skills to potential employers.

Practical Cybersecurity Architecture. A guide to creating and implementing robust designs for cybersecurity architects

Ed Moyle, Diana Kelley

Cybersecurity architects work with others to develop a comprehensive understanding of the business' requirements. They work with stakeholders to plan designs that are implementable, goal-based, and in keeping with the governance strategy of the organization.With this audiobook, you'll explore the fundamentals of cybersecurity architecture: addressing and mitigating risks, designing secure solutions, and communicating with others about security designs. The book outlines strategies that will help you work with execution teams to make your vision a concrete reality, along with covering ways to keep designs relevant over time through ongoing monitoring, maintenance, and continuous improvement. As you progress, you'll also learn about recognized frameworks for building robust designs as well as strategies that you can adopt to create your own designs.By the end of this audiobook, you will have the skills you need to be able to architect solutions with robust security components for your organization, whether they are infrastructure solutions, application solutions, or others.

Mastering Embedded Linux Development. Craft fast and reliable embedded solutions with Linux 6.6 and The Yocto Project 5.0 (Scarthgap) - Fourth Edition

Frank Vasquez, Chris Simmonds

Mastering Embedded Linux Development is designed to be both a learning resource and a reference for your embedded Linux projects.In this fourth edition, you'll learn the fundamental elements that underpin all embedded Linux projects: the toolchain, the bootloader, the kernel, and the root filesystem. First, you will download and install a pre-built toolchain. After that, you will cross-compile each of the remaining three elements from scratch and learn to automate the process using Buildroot and the Yocto Project. The book progresses with coverage of over-the-air software updates and rapid prototyping with add-on boards. Two new chapters tackle modern development practices, including Python packaging and deploying containerized applications. These are followed by a chapter on writing multithreaded code and another on techniques to manage memory efficiently. The final chapters demonstrate how to debug your code, whether it resides in user space or in the Linux kernel itself. In addition to GNU debugger (GDB), the book also covers the different tracers and profilers that are available for Linux so that you can quickly pinpoint any performance bottlenecks in your system.By the end of this book, you will be able to create efficient and secure embedded devices with Linux that will delight your users.

Cloud Observability with Azure Monitor. A practical guide to monitoring your Azure infrastructure and applications using industry best practices

José Ángel Fernández, Manuel Lázaro Ramírez

Cloud observability is complex and costly due to the use of hybrid and multi-cloud infrastructure as well as various Azure tools, hampering IT teams’ ability to monitor and analyze issues. The authors distill their years of experience with Microsoft to share the strategic insights and practical skills needed to optimize performance, ensure reliability, and navigate the dynamic landscape of observability on Azure.You’ll get an in-depth understanding of cloud observability and Azure Monitor basics, before getting to grips with the configuration and optimization of data sources and pipelines for effective monitoring. You’ll learn about advanced data analysis techniques using metrics and the Kusto Query Language (KQL) for your logs, design proactive incident response strategies with automated alerts, and visualize reports via dashboards. Using hands-on examples and best practices, you’ll explore the integration of Azure Monitor with Azure Arc and third-party tools, such as Datadog, Elastic Stack, or Dynatrace. You’ll also implement artificial intelligence for IT Operations (AIOps) and secure monitoring for hybrid and multi-cloud environments, aligned with emerging trends.By the end of this book, you’ll be able to develop robust and cost-optimized observability solutions for monitoring your Azure infrastructure and apps using Azure Monitor.

Learning Continuous Integration with Jenkins. An end-to-end guide to creating operational, secure, resilient, and cost-effective CI/CD processes - Third Edition

Nikhil Pathania

This updated edition of Learning Continuous Integration with Jenkins is your one-stop guide to implementing CI/CD with Jenkins, addressing crucial technologies such as cloud computing, containerization, Infrastructure as Code, and GitOps. Tailored to both beginners and seasoned developers, the book provides a practical path to mastering a production-grade, secure, resilient, and cost-effective CI/CD setup.Starting with a detailed introduction to the fundamental principles of CI, this book systematically takes you through setting up a CI environment using Jenkins and other pivotal DevOps tools within the CI/CD ecosystem. You’ll learn to write pipeline code with AI assistance and craft your own CI pipeline. With the help of hands-on tutorials, you’ll gain a profound understanding of the CI process and Jenkins’ robust capabilities. Additionally, the book teaches you how to expand your CI pipeline with automated testing and deployment, setting the stage for continuous deployment. To help you through the complete software delivery process, this book also covers methods to ensure that your CI/CD setup is maintainable across teams, secure, and performs optimally.By the end of the book, you’ll have become an expert in implementing and optimizing CI/CD setups across diverse teams.

Principles of Data Science. A beginner's guide to essential math and coding skills for data fluency and machine learning - Third Edition

Sinan Ozdemir

Principles of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights.Starting with cleaning and preparation, you’ll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you’ll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data.With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You’ll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you’ll explore medium-level data governance, including data provenance, privacy, and deletion request handling.By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT.

Microsoft Power Apps Cookbook. Build user-friendly apps, troubleshoot challenges, and navigate the evolving Power Apps landscape - Third Edition

Eickhel Mendoza

In the rapidly evolving world of low-code development, Microsoft Power Apps stands out as a powerful platform for building custom business solutions. Microsoft Power Apps Cookbook, 3rd Edition, is your hands-on guide to mastering this platform. Through a collection of step-by-step recipes, this updated edition helps you navigate the latest features, such as AI-powered Microsoft Copilot and custom UI elements while empowering you to build efficient and scalable apps.This book emphasizes practical solutions, guiding app makers through building everything from canvas apps to complex data integrations. You will learn how to streamline repetitive tasks using Robotic Process Automation (RPA) and explore how to create external-facing websites using Microsoft Power Pages while handling data management with Dataverse and extending app functionality with the Power Apps Component Framework.Whether you're extending your app's capabilities with custom components or integrating advanced AI features, Microsoft Power Apps Cookbook equips you with the knowledge and skills to take your app development to the next level.

Data Science with .NET and Polyglot Notebooks. Programmer's guide to data science using ML.NET, OpenAI, and Semantic Kernel

Matt Eland

As the fields of data science, machine learning, and artificial intelligence rapidly evolve, .NET developers are eager to leverage their expertise to dive into these exciting domains but are often unsure of how to do so. Data Science in .NET with Polyglot Notebooks is the practical guide you need to seamlessly bring your .NET skills into the world of analytics and AI. With Microsoft’s .NET platform now robustly supporting machine learning and AI tasks, the introduction of tools such as .NET Interactive kernels and Polyglot Notebooks has opened up a world of possibilities for .NET developers. This book empowers you to harness the full potential of these cutting-edge technologies, guiding you through hands-on experiments that illustrate key concepts and principles. Through a series of interactive notebooks, you’ll not only master technical processes but also discover how to integrate these new skills into your current role or pivot to exciting opportunities in the data science field. By the end of the book, you’ll have acquired the necessary knowledge and confidence to apply cutting-edge data science techniques and deliver impactful solutions within the .NET ecosystem.

LLVM Code Generation. A deep dive into compiler backend development

Quentin Colombet, Kristof Beyls

The LLVM infrastructure is a popular compiler ecosystem widely used in the tech industry and academia. This technology is crucial for both experienced and aspiring compiler developers looking to make an impact in the field. Written by Quentin Colombet, a veteran LLVM contributor and architect of the GlobalISel framework, this book provides a primer on the main aspects of LLVM, with an emphasis on its backend infrastructure; that is, everything needed to transform the intermediate representation (IR) produced by frontends like Clang into assembly code and object files.You’ll learn how to write an optimizing code generator for a toy backend in LLVM. The chapters will guide you step by step through building this backend while exploring key concepts, such as the ABI, cost model, and register allocation. You’ll also find out how to express these concepts using LLVM's existing infrastructure and how established backends address these challenges. Furthermore, the book features code snippets that demonstrate the actual APIs.By the end of this book, you’ll have gained a deeper understanding of LLVM. The concepts presented are expected to remain stable across different LLVM versions, making this book a reliable quick reference guide for understanding LLVM.

Mastering Windows 365. Deploy and Manage Cloud PCs and Windows 365 Link devices, Copilot with Intune, and Intune Suite - Second Edition

Christiaan Brinkhoff, Sandeep Patnaik, Morten Pedholt, Scott Manchester, ...

Windows 365 Cloud PC continues to evolve, integrating AI-driven management, enhanced security, and expanded capabilities to provide a seamless cloud-based Windows experience. This second edition builds on the foundation of the first, incorporating new content on Intune Suite, Copilot+ AI PCs, Windows App, and advanced security with Security Copilot to help IT professionals deploy, manage, and optimize Windows 365 Cloud PCs effectively.This edition expands beyond the basics, covering Intune Suite’s role in optimizing and securing deployments, new methods for application management and delivery, and insights into Windows 365 Link for hybrid cloud environments. You’ll also explore AI-powered administration with Security Copilot, providing intelligent security management and automation.Written by experts from the Windows 365 product team and a Microsoft MVP, this book provides practical guidance, best practices, and real-world insights to help you master modern Windows cloud management. Whether you’re working with Windows 365, Intune Suite, or AI-powered administration, this guide equips you with the latest tools and strategies to stay ahead in cloud computing.

Journey to Become a Google Cloud Machine Learning Engineer. Build the mind and hand of a Google Certified ML professional

Dr. Logan Song

This book aims to provide a study guide to learn and master machine learning in Google Cloud: to build a broad and strong knowledge base, train hands-on skills, and get certified as a Google Cloud Machine Learning Engineer.The book is for someone who has the basic Google Cloud Platform (GCP) knowledge and skills, and basic Python programming skills, and wants to learn machine learning in GCP to take their next step toward becoming a Google Cloud Certified Machine Learning professional.The book starts by laying the foundations of Google Cloud Platform and Python programming, followed the by building blocks of machine learning, then focusing on machine learning in Google Cloud, and finally ends the studying for the Google Cloud Machine Learning certification by integrating all the knowledge and skills together.The book is based on the graduate courses the author has been teaching at the University of Texas at Dallas. When going through the chapters, the reader is expected to study the concepts, complete the exercises, understand and practice the labs in the appendices, and study each exam question thoroughly. Then, at the end of the learning journey, you can expect to harvest the knowledge, skills, and a certificate.

Modern Network Observability. A hands-on approach using open source tools such as Telegraf, Prometheus, and Grafana

David Flores, Christian Adell, Josh VanDeraa, Eric Chou, ...

As modern IT services and software architectures such as microservices rely increasingly on network performance, the relevance of networks has never been greater. Network observability has emerged as a critical evolution of traditional monitoring, providing the deep visibility needed to manage today’s complex, dynamic environments. In Modern Network Observability, authors David Flores, Christian Adell, and Josh VanDeraa share their extensive experience to guide you through building and deploying a flexible observability stack using open-source tools.This book begins by addressing the limitations of monolithic monitoring solutions, showing you how to transform them into a composable, flexible observability stack. Through practical implementations, you’ll learn how to collect, normalize, and analyze network data from diverse sources, build intuitive dashboards, and set up actionable alerts that help you stay ahead of potential issues. Later, you’ll cover advanced topics, such as integrating observability data into your network automation strategy, ensuring your network operations align with business objectives.By the end of this book, you'll be able to proactively manage your network, minimize downtime, and ensure resilient, efficient, and future-proof operations.

Data Structures and Algorithms with the C++ STL. A guide for modern C++ practitioners

John Farrier

While the Standard Template Library (STL) offers a rich set of tools for data structures and algorithms, navigating its intricacies can be daunting for intermediate C++ developers without expert guidance. This book offers a thorough exploration of the STL’s components, covering fundamental data structures, advanced algorithms, and concurrency features.Starting with an in-depth analysis of the std::vector, this book highlights its pivotal role in the STL, progressing toward building your proficiency in utilizing vectors, managing memory, and leveraging iterators. The book then advances to STL’s data structures, including sequence containers, associative containers, and unordered containers, simplifying the concepts of container adaptors and views to enhance your knowledge of modern STL programming. Shifting the focus to STL algorithms, you’ll get to grips with sorting, searching, and transformations and develop the skills to implement and modify algorithms with best practices. Advanced sections cover extending the STL with custom types and algorithms, as well as concurrency features, exception safety, and parallel algorithms.By the end of this book, you’ll have transformed into a proficient STL practitioner ready to tackle real-world challenges and build efficient and scalable C++ applications.

Learn Microsoft Fabric. A practical guide to performing data analytics in the era of artificial intelligence

Arshad Ali, Bradley Schacht

Discover the capabilities of Microsoft Fabric, the premier unified solution designed for the AI era, seamlessly combining data integration, OneLake, transformation, visualization, universal security, and a unified business model. This book provides an overview of Microsoft Fabric, its components, and the wider analytics landscape.In this book, you'll explore workloads such as Data Factory, Synapse Data Engineering, data science, data warehouse, real-time analytics, and Power BI. You’ll learn how to build end-to-end lakehouse and data warehouse solutions using the medallion architecture, unlock the real-time analytics, and implement machine learning and AI models. As you progress, you’ll build expertise in monitoring workloads and administering Fabric across tenants, capacities, and workspaces. The book also guides you step by step through enhancing security and governance practices in Microsoft Fabric and implementing CI/CD workflows with Azure DevOps or GitHub. Finally, you’ll discover the power of Copilot, an AI-driven assistant that accelerates your analytics journey.By the end of this book, you’ll have unlocked the full potential of AI-driven data analytics, gaining a comprehensive understanding of the analytics landscape and mastery over the essential concepts and principles of Microsoft Fabric.

Artificial Intelligence for Robotics. Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks - Second Edition

Francis X. Govers III, Dr. Kamesh Namuduri

Unlock the potential of your robots by enhancing their perception with cutting-edge artificial intelligence and machine learning techniques. From neural networks to computer vision, this second edition of the book equips you with the latest tools, new and expanded topics such as object recognition and creating artificial personality, and practical use cases to create truly smart robots.Starting with robotics basics, robot architecture, control systems, and decision-making theory, this book presents systems-engineering methods to design problem-solving robots with single-board computers. You'll explore object recognition using YOLO and genetic algorithms to teach your robot to identify and pick up objects, leverage natural language processing to give your robot a voice, and master neural networks to classify and separate objects and navigate autonomously, before advancing to guiding your robot arms using reinforcement learning and genetic algorithms. The book also covers path planning and goal-oriented programming to prioritize your robot's tasks, showing you how to connect all software using Python and ROS 2 for a seamless experience.By the end of this book, you'll have learned how to transform your robot into a helpful assistant with NLP and give it an artificial personality, ready to tackle real-world tasks and even crack jokes.

Data Governance Handbook. A practical approach to building trust in data

Wendy S. Batchelder

2.5 quintillion bytes! This is the amount of data being generated every single day across the globe. As this number continues to grow, understanding and managing data becomes more complex. Data professionals know that it’s their responsibility to navigate this complexity and ensure effective governance, empowering businesses with the right data, at the right time, and with the right controls.If you are a data professional, this book will equip you with valuable guidance to conquer data governance complexities with ease. Written by a three-time chief data officer in global Fortune 500 companies, the Data Governance Handbook is an exhaustive guide to understanding data governance, its key components, and how to successfully position solutions in a way that translates into tangible business outcomes.By the end, you’ll be able to successfully pitch and gain support for your data governance program, demonstrating tangible outcomes that resonate with key stakeholders.