Wydawca: Packt Publishing
Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools. As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.
3449
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Microsoft System Center Virtual Machine Manager 2012 Cookbook. Over 60 recipes for the administration and management of Microsoft System Center Virtual Machine Manager 2012 SP1

EDVALDO ALESSANDRO CARDOSO

Microsoft System Center 2012 is a comprehensive IT infrastructure, virtualization, and cloud management platform. With System Center 2012, you can more easily and efficiently manage your applications and services across multiple hypervisors as well as across public and private cloud infrastructures to deliver flexible and cost-effective IT services for your business.This cookbook covers architecture design and planning and is full of deployment tips, techniques, and solutions designed to show users how to improve VMM 2012 in a real world scenario. It will guide you to create, deploy, and manage your own Private Cloud with a mix of Hypervisors: Hyper-V, Vmware ESXi, and Citrix XenServer. It also includes the VMM 2012 SP1 features.This book is a cookbook that covers architecture design, planning and is full of deployment tips, techniques and solutions designed to show users how to improve VMM 2012 in a real world scenario. It will guide you to create, deploy and manage your own Private Cloud with a mix of Hypervisors : Hyper-V, Vmware ESXi and Citrix XenServer.

3450
Ebook

The Definitive Guide to Google Vertex AI. Accelerate your machine learning journey with Google Cloud Vertex AI and MLOps best practices

Jasmeet Bhatia, Kartik Chaudhary

While AI has become an integral part of every organization today, the development of large-scale ML solutions and management of complex ML workflows in production continue to pose challenges for many. Google’s unified data and AI platform, Vertex AI, directly addresses these challenges with its array of MLOPs tools designed for overall workflow management.This book is a comprehensive guide that lets you explore Google Vertex AI’s easy-to-advanced level features for end-to-end ML solution development. Throughout this book, you’ll discover how Vertex AI empowers you by providing essential tools for critical tasks, including data management, model building, large-scale experimentations, metadata logging, model deployments, and monitoring. You’ll learn how to harness the full potential of Vertex AI for developing and deploying no-code, low-code, or fully customized ML solutions. This book takes a hands-on approach to developing u deploying some real-world ML solutions on Google Cloud, leveraging key technologies such as Vision, NLP, generative AI, and recommendation systems. Additionally, this book covers pre-built and turnkey solution offerings as well as guidance on seamlessly integrating them into your ML workflows.By the end of this book, you’ll have the confidence to develop and deploy large-scale production-grade ML solutions using the MLOps tooling and best practices from Google.

3451
Ebook

Machine Learning Security with Azure. Best practices for assessing, securing, and monitoring Azure Machine Learning workloads

Georgia Kalyva, George Kavvalakis

With AI and machine learning (ML) models gaining popularity and integrating into more and more applications, it is more important than ever to ensure that models perform accurately and are not vulnerable to cyberattacks. However, attacks can target your data or environment as well. This book will help you identify security risks and apply the best practices to protect your assets on multiple levels, from data and models to applications and infrastructure.This book begins by introducing what some common ML attacks are, how to identify your risks, and the industry standards and responsible AI principles you need to follow to gain an understanding of what you need to protect. Next, you will learn about the best practices to secure your assets. Starting with data protection and governance and then moving on to protect your infrastructure, you will gain insights into managing and securing your Azure ML workspace. This book introduces DevOps practices to automate your tasks securely and explains how to recover from ML attacks. Finally, you will learn how to set a security benchmark for your scenario and best practices to maintain and monitor your security posture.By the end of this book, you’ll be able to implement best practices to assess and secure your ML assets throughout the Azure Machine Learning life cycle.

3452
Ebook

Unleashing the Power of UX Analytics. Proven techniques and strategies for uncovering user insights to deliver a delightful user experience

Jeff Hendrickson, Travis Wissink

UX analytics is a field that recognizes the significance of understanding human behavior and emotions in designing user experiences. It goes beyond mere metrics and embraces a people-centric approach. With the help of this comprehensive guide, you’ll acquire essential skills, knowledge, and techniques to establish a top-notch UX analytics practice.Unleashing the Power of UX Analytics will equip you with the strategies and tactics necessary to effectively collect, analyze, and interpret data, empowering you to make informed decisions that enhance the overall user experience. It emphasizes the importance of empathy in comprehending user needs and desires, enabling you to create meaningful and impactful design solutions. As you advance, this book walks you through the entire UX analytics process, from setting goals and defining key performance indicators (KPIs) to implementing various research methods and tools. You'll gain insights into user interview best practices, usability testing, and techniques for gathering qualitative and quantitative data.Armed with the knowledge of data analysis and interpretation, you'll be able to uncover patterns, trends, and user preferences to make data-driven decisions.

3453
Ebook

Service Worker Development Cookbook. Click here to enter text

Sean Amarasinghe

It would be nice to have web apps that work offline and send push notifications. This is now possible with Service Workers, which can add native-like functionality to your web apps without requiring a download. This book will get your mobile and web apps functioning without Internet connectivity, improve performance and network interaction in order to increase the level of availability, and show you how to build performant applications that seamlessly integrate with third-party APIs.We’ll show you how to add Service Worker functionality to web apps and sites, access offline content through basic and advanced techniques, and build powerful interactive system notifications. We’ll also teach you about cache functionality and assets to provide immediate load even over narrow connections. We conclude by giving you various tips to improve app performance, including the background sync technique. By the end of this book, you’ll know build high performing and faster web and mobile applications with Service Workers.

3454
Ebook

Agile Machine Learning with DataRobot. Automate each step of the machine learning life cycle, from understanding problems to delivering value

Bipin Chadha, Sylvester Juwe

DataRobot enables data science teams to become more efficient and productive. This book helps you to address machine learning (ML) challenges with DataRobot's enterprise platform, enabling you to extract business value from data and rapidly create commercial impact for your organization.You'll begin by learning how to use DataRobot's features to perform data prep and cleansing tasks automatically. The book then covers best practices for building and deploying ML models, along with challenges faced while scaling them to handle complex business problems. Moving on, you'll perform exploratory data analysis (EDA) tasks to prepare your data to build ML models and ways to interpret results. You'll also discover how to analyze the model's predictions and turn them into actionable insights for business users. Next, you'll create model documentation for internal as well as compliance purposes and learn how the model gets deployed as an API. In addition, you'll find out how to operationalize and monitor the model's performance. Finally, you'll work with examples on time series forecasting, NLP, image processing, MLOps, and more using advanced DataRobot capabilities.By the end of this book, you'll have learned to use DataRobot's AutoML and MLOps features to scale ML model building by avoiding repetitive tasks and common errors.

3455
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3456
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