Human Aspects of It for the Aged Population
This two-volume set of ITAP 2023, constitutes the refereed proceedings of the 9th International Conference on Human Aspects of IT for the Aged Population, ITAP 2023, held as Part of the 24th International Conference, HCI International 2023, which took place in July 2023 in Copenhagen, Denmark.The total of 1578 papers and 396 posters included in the HCII 2023 proceedings volumes was carefully reviewed and selected from 7472 submissions. The papers of ITAP 2023 Part I are organized in topical sections named: Designing and Assessing the Older Users' Experience; Aging and Social Media; Voice Assistants and Chatbots; Games and Exergames for Older People.
Adaptive Instructional Systems
This book constitutes the refereed proceedings of the 5th International Conference, AIS 2023, held as part of the 25th International Conference, HCI International 2023, which was held virtually in Copenhagen, Denmark in July 2023.The total of 1578 papers and 396 posters included in the HCII 2023 proceedings was carefully reviewed and selected from 7472 submissions. The AIS 2023 proceeding helps to understand the theory and enhance the state-of-practice for a set of technologies (tools and methods) called adaptive instructional systems (AIS). AIS are defined as artificially intelligent, computer-based systems that guide learning experiences by tailoring instruction and recommendations based on the goals, needs, preferences, and interests of each individual learner or team in the context of domain learning objectives.
Hands-On Multi-Cloud Kubernetes
"Hands-On Multi-Cloud Kubernetes" is an essential guide for anyone looking to understand Kubernetes and how it can be used to manage multi-cloud infrastructure. With eight comprehensive chapters, this book provides hands-on experience in setting up Kubernetes clusters, administering deployments and updates, and working with AWS and GCP tools.Readers will learn to work with various powerful tools, including Helm, FluxCD, Virtual Kubelet, Submariner, and KubeFed. With GitOps principles and workflows, they will practice continuous delivery and learn to manage secrets and config maps. They will build and deploy serverless clusters using Virtual Kubelet and learn to scale them across multiple cloud environments. They will even be introduced to cross-cluster networking with Submariner, where they will learn to perform service discovery, load balancing, and monitor networking metrics. Managing multi-cluster Kubernetes can be a daunting task, but with KubeFed, readers will gain the skills necessary to set up and deploy multicluster federations, making it easier than ever to administer their own infrastructure. And with multi-cloud CI/CD pipelines using Jenkins, they will perform end-to-end multi-cloud operations, ensuring their code is delivered quickly and efficiently.Finally, the book covers security in Kubernetes, giving readers the tools and knowledge to configure RBAC, Kubernetes network policies, and secure data over Kubernetes clusters. They will even learn to use Open Policy Agent to manage compliance, ensuring that their infrastructure is powerful and secure.Key LearningsLearn Multi-cloud Kubernetes from fundamentals to advanced concepts and toolsSetting up and managing Kubernetes clusters on multi-cloud infrastructureWorking with powerful tools like Helm, FluxCD, and Virtual KubeletUtilize Submariner for cross-cluster networking, service discovery, and load balancingCI/CD pipelines with Jenkins for end-to-end multi-cloud operationsPractice GitOps principles and workflows for continuous deliveryBuilding and deploying serverless clusters using Virtual KubeletManaging multiple Kubernetes clusters as a single entity with KubeFedSecurity in Kubernetes with RBAC, network policies, and Open Policy Agent Table of ContentIntroduction to Multi-cloud KubernetesKubernetes Cluster Management and DeploymentUsing FluxCDVirtual Kubelet and Serverless ClustersNetworking with SubmarinerMultiCluster Management and FederationMulti-cloud CI/CD PipelinesSecurity in Multi-cloud Kubernetes AudienceThis book is ideal for cloud professionals, the DevOps team, Kubernetes developers, and networking professionals to explore multi-cloud networking, working with multi clusters, deploying Kubernetes, and getting skilled with various innovative Kubernetes tools. Knowing cloud networking or Kubernetes is sufficient to begin with the book.
Excel
Make Excel Your Best Friend - Master Microsoft Excel in 2023 with Step-by-Step Instructions.Do you want to be a pro at Excel and keep up with the changing trends in the market?Do you need to learn how to use Excel from the ground up?Do you need to learn about the fundamentals, features, formulas, and charts for Excel?Excel is one of the most valuable tools and with this guide you'll be able to unlock the full potential of the program.Here's what you can learn: Learn the basics of Excel: A comprehensive look into the Excel UI, formulas, and function and how to use it for problem-solvingCreate Powerful Visualizations with Charts and Graphs: Master the art of data presentation with impressive visualizations that bring complex data to lifeLeverage the Power of Pivot Tables: A complete guide to help you create the most powerful Excel tool to analyze and summarize large data setsGet Expert-Level Knowledge of Excel at Work: Improve your work competencies with advanced Excel featuresLearn to Avoid Common Errors: Tips, tricks, and instructions to avoid the most common Excel mistakesPlus, much more!Don't miss out on this opportunity to master Excel. Get started on your journey to becoming an Excel professional with this comprehensive guide today!
Agile Software Development with C# 4th Edition
This beginner's book aims to introduce you to the field of agile software development with C#. While there are numerous books on both C# and agile methodologies, few teach them together in a single package. This book will help you understand how agile blurs the lines between the roles of analyst, designer, programmer, and tester. By combining C# and agile in one book, this guide allows you to experience all roles through a single journey. At the end of the book, you will find several small C# projects to work on, following agile principles. Collaborating with four or five other readers (e.g., in a college setting) will further benefit your understanding. Please note that this book is not a reference and content will be kept at a minimum. Additionally, it is designed to cater to beginners and is not an in-depth coverage of any specific topic. If you require further details, readers are encouraged to research the web. To maximize your learning experience, this book requires you to type all code, and we do not provide sample code downloads. We understand your time is valuable, but we believe hands-on practice is the best way to learn. Throughout the book, you will be given plenty of exercises under the titles of "Programming Challenge" and "Test Your Understanding." We strongly encourage you to try all exercises as you work through the book. Finally, this fourth edition of the book uses Visual Studio 2022 Community as the development environment. Last but not least, we thank Dr. Youlong Zhuang for reviewing this fourth edition and providing valuable suggestions.
Socially Responsible AI
In the current era, people and society have grown increasingly reliant on artificial intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of humanity flourishes. It also comes with substantial risks for oppression and calamity. In response, researchers and organizations have been working to publish principles and develop AI regulations for the responsible use of AI in consequential application domains. However, these theoretically formulated principles and regulations also need to be turned into actionable algorithms to materialize AI for good.This book introduces a unified perspective of Socially Responsible AI to help bridge conceptual AI principles to responsible AI practice. It begins with an interdisciplinary definition of socially responsible AI and the AI responsibility pyramid. Existing efforts seeking to materialize the mainstream responsible AI principles are then presented. The book also discusses how to leverage advanced AI techniques to address the challenging societal issues through Protecting, Informing, and Preventing, and concludes with open problems and challenges.This book serves as a convenient entry point for researchers, practitioners, and students to understand the problems and challenges of socially responsible AI, and to identify how their areas of expertise can contribute to making AI socially responsible.
Machine Learning Safety
Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises new safety concerns, as machine learning has many specificities that make its behaviour prediction and assessment very different from that for explicitly programmed software systems. This book addresses the main safety concerns with regard to machine learning, including its susceptibility to environmental noise and adversarial attacks. Such vulnerabilities have become a major roadblock to the deployment of machine learning in safety-critical applications. The book presents up-to-date techniques for adversarial attacks, which are used to assess the vulnerabilities of machine learning models; formal verification, which is used to determine if a trained machine learning model is free of vulnerabilities; and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readers' awareness of the potential safety issues regarding machine learning models. In addition, it includes up-to-date techniques for dealing with these issues, equipping readers with not only technical knowledge but also hands-on practical skills.
Generative Deep Learning
Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models. The book starts with the basics of deep learning and progresses to cutting-edge architectures. Through tips and tricks, you'll understand how to make your models learn more efficiently and become more creative. Discover how VAEs can change facial expressions in photos Train GANs to generate images based on your own dataset Build diffusion models to produce new varieties of flowers Train your own GPT for text generation Learn how large language models like ChatGPT are trained Explore state-of-the-art architectures such as StyleGAN2 and ViT-VQGAN Compose polyphonic music using Transformers and MuseGAN Understand how generative world models can solve reinforcement learning tasks Dive into multimodal models such as DALL.E 2, Imagen, and Stable Diffusion This book also explores the future of generative AI and how individuals and companies can proactively begin to leverage this remarkable new technology to create competitive advantage.
Python Essentials for AWS Cloud Developers
A comprehensive guide to implementing Python applications in AWS while learning about key AWS servicesPurchase of the print or Kindle book includes a free PDF eBookKey Features: Gain hands-on experience in AWS services to effectively implement Python programmingUtilize Python with open source libraries to develop data pipelines, APIs, and database applicationsLeverage the power of AWS to create a cloud-based server and use monitoring and logging featuresBook Description: AWS provides a vast variety of services for implementing Python applications, which can pose a challenge for those without an AWS background. This book addresses one of the more predominant problems of choosing the right service and stepping into the implementation of exciting Python apps using AWS.The book begins by showing you how to install Python and create an AWS account, before helping you explore AWS Lambda, EC2, Elastic Beanstalk, and S3 for Python programming. You'll then gain hands-on experience in using these services to build the Python application. As you advance, you'll discover how to debug Python apps using PyCharm, and then start deploying the Python applications on Elastic Beanstalk. You'll also learn how to monitor Python applications using the CloudWatch service, along with creating and publishing APIs on AWS to access the Python application. The concluding chapters will help you get to grips with storing unstructured and semi-structured data using NoSQL and DynamoDB, as well as advance your knowledge using the Glue serverless data integration service in AWS.By the end of this Python book, you'll be able to take your application development skills up a notch with AWS services and advance in your career.What You Will Learn: Understand the fundamentals of AWS services for Python programmingFind out how to configure AWS services to build Python applicationsRun and deploy Python applications using Lambda, EC2, and Elastic BeanstalkProvision EC2 servers on AWS and run Python applicationsDebug and monitor Python applications using PyCharm and CloudWatchUnderstand database operations on AWS by learning about DynamoDB and RDSExplore the API gateway service on AWS using Python to grasp API programmingWho this book is for: This book is for cloud developers, software developers, and IT specialists who want to develop Python applications on AWS as well as learn the concepts underlying AWS services for implementing the applications. Experience in Python programming is needed to be able to implement the applications on AWS.
An Introduction to Neural Data Compression
The goal of data compression is to reduce the number of bits needed to represent useful information. Neural, or learned compression, is the application of neural networks and related machine learning techniques to this task. This monograph aims to serve as an entry point for machine learning researchers interested in compression by reviewing the prerequisite background and representative methods in neural compression. Neural compression is the application of neural networks and other machine learning methods to data compression. Recent advances in statistical machine learning have opened up new possibilities for data compression, allowing compression algorithms to be learned end-to-end from data using powerful generative models such as normalizing flows, variational autoencoders, diffusion probabilistic models, and generative adversarial networks. This monograph introduces this field of research to a broader machine learning audience by reviewing the necessary background in information theory (e.g., entropy coding, rate-distortion theory) and computer vision (e.g., image quality assessment, perceptual metrics), and providing a curated guide through the essential ideas and methods in the literature thus far. Instead of surveying the vast literature, essential concepts and methods in neural compression are covered, with a reader in mind who is versed in machine learning but not necessarily data compression.
The Book on Testing
More than ever, we depend on software to get through our everyday lives. It's embedded in our smartphones, cars, children's toys, and household appliances (even our toasters), and it's transforming our world. This brave new world of technology offers exciting opportunities, but it has never been more important that we recognize and understand the risks to our security and safety. When software goes bad, the consequences can range from the farcical (such as the HealthCare.gov fiasco, in which a highly-touted government website crashed almost immediately upon being launched) to the tragic (as in the case of the Arizona woman who was killed by a self-driving car that didn't recognize her as a pedestrian).Testing is our line of defence against these software-related catastrophes. Yet, for years, it was seen as an afterthought-a chore that developers only carried out because they had to, and which they tried to complete as cheaply and quickly as possible.In The Book on Testing, Alex Rodov leads the reader on a personal and informal tour of the software-testing landscape, focusing on what happens when it isn't done properly. In easy-to-understand language, he offers real-life examples, as well as insights gained from decades of experience, to demonstrate why it doesn't have to be that way. Testing is difficult and can never be perfect. But if it's done well, we'll all be able to sleep better at night.
Artificial Intelligence Model for Prediction of Faecal Coliform Bacteria in Ground Water
An Artificial Intelligence (AI) model for the prediction of faecal coliform bacteria in ground water is a computational tool that uses machine learning algorithms to analyze water quality data and predict the concentration of faecal coliform bacteria in ground water. Faecal coliform bacteria are a type of bacteria commonly found in the intestines of warm-blooded animals, and their presence in ground water can indicate contamination from human or animal waste, which can be harmful to human health.The AI model for prediction of faecal coliform bacteria in ground water may utilize various data sources, including water quality measurements such as pH, temperature, dissolved oxygen, turbidity, and conductivity, as well as geographic and environmental factors such as land use, soil type, and hydrogeology. The model may be trained using historical water quality data, along with other relevant data sources, to learn patterns and relationships between water quality variables and the concentration of faecal coliform bacteria in ground water.Once the AI model is trained, it can be used to predict the concentration of faecal coliform bacteria in ground water based on current or future water quality measurements. This information can be used by water managers, policymakers, and other stakeholders to identify potential sources of contamination, implement mitigation measures, and protect human health and the environment.
Ceh V12 Certified Ethical Hacker Study Guide with 750 Practice Test Questions
The latest version of the official study guide for the in-demand CEH certification, now with 750 Practice Test Questions Information security and personal privacy remains a growing concern for businesses in every sector. And even as the number of certifications increases, the Certified Ethical Hacker, Version 12 (CEH v12) maintains its place as one of the most sought-after and in-demand credentials in the industry. In CEH v12 Certified Ethical Hacker Study Guide with 750 Practice Test Questions, you'll find a comprehensive overview of the CEH certification requirements. Concise and easy-to-follow instructions are combined with intuitive organization that allows you to learn each exam objective in your own time and at your own pace. The Study Guide now contains more end of chapter review questions and more online practice tests. This combines the value from the previous two-book set including a practice test book into a more valuable Study Guide. The book offers thorough and robust coverage of every relevant topic, as well as challenging chapter review questions, even more end of chapter review questions to validate your knowledge, and Exam Essentials, a key feature that identifies important areas for study. There are also twice as many online practice tests included. You'll learn about common attack practices, like reconnaissance and scanning, intrusion detection, DoS attacks, buffer overflows, wireless attacks, mobile attacks, Internet of Things vulnerabilities, and more. It also provides: Practical, hands-on exercises that reinforce vital, real-world job skills and exam competencies Essential guidance for a certification that meets the requirements of the Department of Defense 8570 Directive for Information Assurance positions Complimentary access to the Sybex online learning center, complete with chapter review questions, full-length practice exams, hundreds of electronic flashcards, and a glossary of key terms The CEH v12 Certified Ethical Hacker Study Guide with 750 Practice Test Questions is your go-to official resource to prep for the challenging CEH v12 exam and a new career in information security and privacy.
Pattern Recognition
This book constitutes the refereed proceedings of the 15th Mexican Conference on Pattern Recognition, MCPR 2023, held in Tepic, Mexico, during June 21-24, 2023.The 30 full papers presented in this book were carefully reviewed and selected from 61 submissions. The papers are divided into the following topical sections: pattern recognition and machine learning techniques; deep learning and neural networks; medical applications of pattern recognition; language processing and recognition; and industrial applications of pattern recognition.
FinOps Handbook for Microsoft Azure
Drive financial visibility, set cost optimization goals, and reap savings for your organization with proven practices and invaluable insightsPurchase of the print or Kindle book includes a free PDF eBookKey Features: Build a FinOps team and foster cross-organizational collaboration to optimize costsGain a deep insight into resource usage and rates to unlock the secrets of cost optimizationApply your FinOps expertise to run a successful practice, reinvesting savings into new feature developmentBook Description: To gain a competitive edge in today's unpredictable economic climate, you'll need to unravel the mystery of saving costs on Microsoft Azure Cloud. This book helps you do just that with proven strategies for building, running, and sustaining repeated cost optimization initiatives across your organization. You'll learn how to collaborate with finance, procurement, product, and engineering teams to optimize your cloud spend and achieve cost savings that can make a significant impact on your bottom line.The book begins by showing you how to effectively monitor and manage your cloud usage, identify cost-saving opportunities, and implement changes that'll reduce your overall spend. Whether you're a small start-up or a large enterprise, this book will equip you with the knowledge and skills needed to achieve cost savings and maintain a lean cloud infrastructure. As you advance, you'll find out how to benchmark your current cloud spend and establish a budget for cloud usage. Throughout the chapters, you'll learn how to negotiate with your cloud provider to optimize your rate, allocate cost for the container, and gain a solid understanding of metric-driven cost optimization.By the end of this FinOps book, you'll have become proficient in Azure Cloud financial management with the help of real-world examples, use cases, and scenarios.What You Will Learn: Get the grip of all the activities of FinOps phases for Microsoft AzureUnderstand architectural patterns for interruptible workload on Spot VMsOptimize savings with Reservations, Savings Plans, Spot VMsAnalyze waste with customizable pre-built workbooksWrite an effective financial business case for savingsApply your learning to three real-world case studiesForecast cloud spend, set budgets, and track accuratelyWho this book is for: This book is for cloud governance experts, finance managers, procurement specialists, product developers, and engineering teams looking to get clear and actionable guidance needed to implement all the phases of the FinOps life cycle in the Microsoft Azure context. This book is ideal for anyone with a basic understanding of financial terms, analytics tools, and the Azure cloud.
Hacker Culture A to Z
Hacker culture can be esoteric, but this entertaining reference is here to help. Written by longtime cybersecurity researcher and writer Kim Crawley, this fun reference introduces you to key people and companies, fundamental ideas, and milestone films, games, and magazines in the annals of hacking. From airgapping to phreaking to zombie malware, grasping the terminology is crucial to understanding hacker culture and history. If you're just getting started on your hacker journey, you'll find plenty here to guide your learning and help you understand the references and cultural allusions you come across. More experienced hackers will find historical depth, wry humor, and surprising facts about familiar cultural touchstones. Understand the relationship between hacker culture and cybersecurity Get to know the ideas behind the hacker ethos, like "knowledge should be free"? Explore topics and publications central to hacker culture, including 2600 Magazine Appreciate the history of cybersecurity Learn about key figures in the history of hacker culture Understand the difference between hackers and cybercriminals
PMP Exam Prep Guide 101
If you're planning to take the Project Management Professional (PMP) certification exam, you know how challenging it can be. The exam covers a broad range of project management topics and requires you to have a deep understanding of project management principles, concepts, and best practices.The PMP Exam Prep Guide 101 is a practical guide that is designed to help you prepare for the PMP exam with confidence. This comprehensive guide provides a step-by-step approach to exam preparation and covers all the topics that are tested on the PMP exam.The guide starts with an overview of the PMP exam structure, format, and eligibility requirements, and then dives into the details of the PMBOK (Project Management Body of Knowledge) guide. It includes hundreds of practice questions, quizzes, and mock exams to assess your knowledge and identify areas of improvement.You'll also find tips, tricks, and techniques for effective exam preparation and time management, along with strategies for approaching situational and scenario-based questions on the exam. The guide is packed with real-world examples and case studies to reinforce concepts and best practices, and it provides guidance on how to apply project management principles and techniques in various scenarios.In addition to the print version, the PMP Exam Prep Guide 101 comes with access to an online platform that includes videos, webinars, and forums for additional support and learning. Whether you're a seasoned project manager or new to the field, this guide is a valuable resource that will help you master the art of project management and pass the PMP certification exam with flying colors.
Robotics for Cell Manipulation and Characterization
Robotics for Cell Manipulation and Characterization provides fundamental principles underpinning robotic cell manipulation and characterization, state-of-the-art technical advances in micro/nano robotics, new discoveries of cell biology enabled by robotic systems, and their applications in clinical diagnosis and treatment. This book covers several areas, including robotics, control, computer vision, biomedical engineering and life sciences using understandable figures and tables to enhance readers' comprehension and pinpoint challenges and opportunities for biological and biomedical research.
SwiftUI Apprentice (Second Edition)
Learn iOS Development Using SwiftUIYou've heard about Apple's hot new declarative user interface SDK - SwiftUI - and are ready to try your hand at iOS development. But, you have no idea where to begin.SwiftUI Apprentice to the rescue! This book will guide you through the first steps of your journey as you learn to build beautiful iOS apps.Who This Book Is ForThis book for developers who are new to iOS and SwiftUI who are looking for a step-by-step path to learning.Topics Covered in SwiftUI ApprenticeUsing Xcode: Learn how to use Xcode - Apple's integrated development environment - to code, build and debug your iOS apps.Planning and Prototyping: Learn how to plan and prototype apps using SwiftUI. Once you're happy with the prototype, you'll fill out the implementation into a full-featured app with a beautiful, professionally-designed user interface.Managing Assets: Discover how to manage app assets, such as colors and images, so your app looks good on all iOS devices from the smallest iPod Touch to the largest iPad.SwiftUI Data Flow: See how to manage data within a SwiftUI app so the user interface updates automatically as that data changes.Data Persistence: Explore multiple strategies for persisting an app's data. Understand the pros and cons of several approaches so you can decide the best solution for your own apps.Networking: Learn to access REST APIs so your app can use internet resources to enhance your app's user experience.One thing you can count on: After reading this book, you'll be prepared to create your own iOS apps using SwiftUI.
Modeling Decisions for Artificial Intelligence
This book constitutes the refereed proceedings of the 20th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2023, held in Ume疇, Sweden, during June19-22,2023.The 17 papers presented in this volume were carefully reviewed and selected from 28 submissions. Additionally, 1 invited paper were included. The papers discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search.The papers are organized in the following topical sections: Decision making and uncertainty; Machine Learning and data science; and Data privacy.
Designing Ai Companions
Designing AI companions can be a daunting task. In this comprehensive guide, you will find everything you need to know about designing AI companions. From understanding your user's needs to designing engaging personalities and delightful interactions. The book highlights the research and user testing outcomes as best practices for reducing the complexity of technology and creating trustful connections between human and artificial intelligence. It will help and guide everyone, who is interested in designing new experiences, products, or services with artificial intelligence to design companions that are both personable and helpful by understanding the expressions of emotions and empathy with psychological, cognitive, and social theories.
SeniorITy
Do you feel frustrated and left behind as every aspect of daily life - from banking and shopping to health and communication - becomes increasingly dependent on technology, the internet, and artificial intelligence (AI)? SeniorITy empowers us as we age, and those hesitant to engage with new technologies, by exploring the positives of becoming knowledgable and fully connected online. Accepting technological advances can help you live a long, healthy, and more rewarding life. Learn how to: - Understand why you find it difficult to engage with the digital world - Overcome frustration with the technology necessary for everyday life - Make decisions about the best tech options for you - Protect yourself and your data online - Embrace digital advances that can increase independence and improve quality of life
Designing Ai Companions
Designing AI companions can be a daunting task. In this comprehensive guide, you will find everything you need to know about designing AI companions. From understanding your user's needs to designing engaging personalities and delightful interactions. The book highlights the research and user testing outcomes as best practices for reducing the complexity of technology and creating trustful connections between human and artificial intelligence. It will help and guide everyone, who is interested in designing new experiences, products, or services with artificial intelligence to design companions that are both personable and helpful by understanding the expressions of emotions and empathy with psychological, cognitive, and social theories.
AI for Beginners
This essential guide to Artificial Intelligence is perfect for anyone looking to explore the power of AI in their field. With a step-by-step approach, this book will take you from beginner to expert in no time, covering all the basics of AI, including machine learning, natural language processing, and computer vision. Packed with practical examples and real-world applications, this book provides a hands-on approach to AI, giving you the skills you need to build intelligent systems that can solve complex problems. With its clear, concise writing style and easy-to-follow instructions, this book is perfect for beginners and experts alike. Whether you're looking to improve your business operations, automate tedious tasks, or create cutting-edge products, this book is your ultimate guide to getting started with AI. So why wait? Start your AI journey today and unleash the power of artificial intelligence!
Writing API Tests with Karate
Unlock the full potential of Karate with this comprehensive guide to effortlessly setup, write, run, optimize, and report test resultsPurchase of the print or Kindle book includes a free PDF eBookKey Features: Explore the capabilities of the Karate framework for effective software testingLearn how to integrate Karate tests into projects and CI/CD pipelinesExplore lesser-known Karate modules such as Karate UI and Karate GatlingBook Description: Software in recent years is moving away from centralized systems and monoliths to smaller, scalable components that communicate with each other through APIs. Testing these communication interfaces is becoming increasingly important to ensure the security, performance, and extensibility of the software. A powerful tool to achieve safe and robust applications is Karate, an easy-to-use, and powerful software testing framework.In this book, you'll work with different modules of karate to get tailored solutions for modern test challenges. You'll be exploring interface testing, UI testing as well as performance testing.By the end of this book, you'll be able to use the Karate framework in your software development lifecycle to make your APIs and applications robust and trustworthy.What You Will Learn: Understand the basic concepts of Karate and its functionalityIntegrate and use it effectively to solve your testing needsExtend Karate and customize its functionality for your use casesExplore different testing methods and their use casesRun your tests to check the software development lifecycleGet to know more about Karate's UI and performance test approachesWho this book is for: This book is for QA engineers and developers who are familiar with APIs and want to make them safer and more secure by applying automated tests with the help of a lightweight and modern framework - Karate.
Updates on Software Usability
Updates on Software Usability is a collection of high-quality contributions for developers and non-developers alike. Beyond the preliminaries, the book is organized into two other parts: "Designing for Usability" and "Testing for Usability". The chapters in the second section, "Designing for Usability", offer valuable insights and practical guidance to take into account during the early stages of product conception and development. On the other hand, the chapters in the third section, "Testing for Usability", reflect and formalize software usability's evaluation and validation processes. These two complementary views on the subject make this book a balanced and comprehensive volume, which the reader will undoubtedly find both interesting and useful.
Intelligent Video Surveillance - New Perspectives
The development of new technologies based on artificial intelligence and computer vision, together with the possibility of connecting different devices together in real-time, has enabled the development and progress of intelligent video surveillance. Thanks to IoT technologies, high-resolution cameras can be networked to monitor their territory, collect recordings and have them analyzed by artificial intelligence systems trained to identify critical situations. This book discusses new achievements in intelligent video surveillance solutions and their future prospects.
Embedded Artificial Intelligence
Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge. Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources. Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO. The book's content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries.
Design Science Research for a New Society: Society 5.0
This book constitutes the proceedings of the 18th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2023, which was held in Pretoria, South Africa, from May 31-June 2, 2023.The 29 full papers presented in this volume were carefully reviewed and selected from 81 submissions. The papers are organized in the following topical sections: Design-oriented Research for Society 5.0 (Theme Track); Design of Systems Using Emerging Technologies; Human-Centered Artificial Intelligence (HCAI); Healthcare Systems and Quality of Life; Innovation and Entrepreneurship; Emerging DSR Methods and Processes; Education and DRS; Human Safety and Cybersecurity; Co-Desing and Collective Creativity for Addressing Grand Challenges; and Sustainability and Responsible Design.
Building Site Log for Foreman
Building Site Log for Foreman, Help you To Record Construction Project Name, Visitors, Schedule, Problems, Safety Issues, Summary of Work, Employee and many many more ...Our Log designed for Foremen to provides a clear, consistent, complete format to make record-keeping easier.Get your copy today!Features Building Site Log for Foreman: ✔ Good quality paper with glossy modern cover✔ Double-sided pages, to improve thinness and handling✔ Size 6 x 9 inches✔ Book with 120 Pages
Data Fabric and Data Mesh Approaches with AI
Understand modern data fabric and data mesh concepts using AI-based self-service data discovery and delivery capabilities, a range of intelligent data integration styles, and automated unified data governance--all designed to deliver "data as a product" within hybrid cloud landscapes.This book teaches you how to successfully deploy state-of-the-art data mesh solutions and gain a comprehensive overview on how a data fabric architecture uses artificial intelligence (AI) and machine learning (ML) for automated metadata management and self-service data discovery and consumption. You will learn how data fabric and data mesh relate to other concepts such as data DataOps, MLOps, AIDevOps, and more. Many examples are included to demonstrate how to modernize the consumption of data to enable a shopping-for-data (data as a product) experience.By the end of this book, you will understand the data fabric concept and architecture as it relates to themes such as automated unifieddata governance and compliance, enterprise information architecture, AI and hybrid cloud landscapes, and intelligent cataloging and metadata management. What You Will LearnDiscover best practices and methods to successfully implement a data fabric architecture and data mesh solutionUnderstand key data fabric capabilities, e.g., self-service data discovery, intelligent data integration techniques, intelligent cataloging and metadata management, and trustworthy AIRecognize the importance of data fabric to accelerate digital transformation and democratize data accessDive into important data fabric topics, addressing current data fabric challengesConceive data fabric and data mesh concepts holistically within an enterprise contextBecome acquainted with the business benefits of data fabric and data mesh Who This Book Is ForAnyone who is interested in deploying modern data fabric architectures and data mesh solutions within an enterprise, including IT and business leaders, data governance and data office professionals, data stewards and engineers, data scientists, and information and data architects. Readers should have a basic understanding of enterprise information architecture.
Machine Learning, Animated
The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. Machine Learning, Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize, adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step, to the final converged parameters and predictions.This book teaches readers to create their own neural networks with dense and convolutional layers, and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning, witnessing AI achieve super-human performance in Atari games such as Breakout, Space Invaders, Seaquest and Beam Rider.Written in a clear and concise style, illustrated with animations and images, this book is particularly appealing to readers with no background in computer science, mathematics or statistics.Access the book's repository at: https: //github.com/markhliu/MLA
Secure Shell
An OpenSSH SSH manual compilation. The manuals cover the OpenSSH SSH client; configuration file; authentication agent; key generator, manager, and converter; authentication agent's private key identity adder; daemon; daemon configuration file; public key gatherer; and host-based authentication helper. They also cover the OpenSSH SFTP server subsystem, secure file transfer program, and secure copy program. Edition 1 is current as of October 2022.
Machine Learning Based Prediction Techniques
Machine Learning based Prediction Techniques is a book for those who wanted to learn basics of Machine Learning and for those interested in undertaking projects, research, etc. The contents of book starts from the basics and extends to advanced content in a systematic manner. At the end of the book, learners will be able to develop their own predictive machine leaning based automated system.This book is useful for M.phil. and Ph.D. students doing research in the area of biomedical signal processing like EEG brain signal. It is also useful for physicians dealing with epilepsy patients. By continuously recording the patient's EEG and using this Machine Learning based prediction techniques, the onset of an epileptic episode can be predicted 25 to 30 minutes earlier and physician able to reset the brain condition dynamically by giving proper treatment to the patients and avoiding the occurrence of the seizure.
Predicting the Unknown
As a society, we're in a constant struggle to control uncertainty and predict the unknown. Quite often, we think of scientific fields and theories as being separate from each other. But a more careful investigation can uncover the common thread that ties many of those together. From ChatGPT, to Amazon's Alexa, to Apple's Siri, data science, and computer science have become part of our lives. In the meantime, the demand for data scientists has grown, as the field has been increasingly called the "sexiest profession." This book attempts to specifically cover this gap in literature between data science, machine learning and artificial intelligence (AI). How was uncertainty approached historically, and how has it evolved since? What schools of thought exist in philosophy, mathematics, and engineering, and what role did they play in the development of data science? It uses the history of data science as a stepping stone to explain what the future might hold. Predicting the Unknown provides the framework that will help you understand where AI is headed, and how to best prepare for the world that's coming in the next few years, both as a society and within a business. It is not technical and avoids equations or technical explanations, yet is written for the intellectually curious reader, and the technical expert interested in the historical details that can help contextualize how we got here. What You'll LearnExplore the bigger picture of data science and see how to best anticipate future changes in that fieldUnderstand machine learning, AI, and data scienceExamine data science and AI through engaging historical and human-centric narratives Who is This Book ForBusiness leaders and technology enthusiasts who are trying to understand how to think about data science and AI
Human Work Interaction Design. Artificial Intelligence and Designing for a Positive Work Experience in a Low Desire Society
This book constitutes the thoroughly refereed post-conference proceedings of the 6th IFIP WG 13.6 Working Conference on Human Work Interaction Design, HWID 2021, held in Beijing, China, in May, 2021. The 10 revised and extended full papers presented were carefully selected for inclusion in this volume. The papers deal with the analysis and interaction design of a variety of complex work and life contexts found in different business and application domains. They focus on interaction design for work engagement taking usability of interactive systems to the next level by providing employees pleasurable and meaningful experiences via the tools used at work. The papers are organized the following topical sub-headings: Trends in human Work Interaction Design; Workplace & work experience Analysis for Interaction Design; and Artificial Intelligence (AI) for Human Work.
Human-Centered Artificial Intelligence
The 18th European Advanced Course on AI (ACAI) took place in Berlin on 11-15 October 2021, organized by the European project Humane-AI Net in collaboration with the European AI Association (EURAI). The school included tutorials on different topics, which were selected through an open call to top European AI researchers. In addition, the school also included 4 invited talks, a student poster presentation, and a mentorship program. This volume contains 21 tutorial chapters organized according to the following themes: human-centered AI; human-centered machine learning; explainable AI; ethics, law, and the societal aspects of AI; argumentation; and social simulation. The contributions include learning objectives, reading lists, and links to further resources.
Humanizing AI
As artificial intelligence (AI) continues to advance at an unprecedented pace, humanity is faced with a rapidly evolving landscape that poses both incredible opportunities and daunting challenges. In this thought-provoking exploration of the intersection of AI and humanity, ChatGPT, a large language model trained by OpenAI, engages in a candid and insightful dialogue with a human interlocutor about the ethical, social, and political implications of this rapidly changing landscape.From the promise of AI to transform the world for the better, to the potential risks of losing control over intelligent systems, ChatGPT and his interlocutor delve deep into the complexities and nuances of this complex topic. They explore the ways in which AI is already transforming the economy, healthcare, education, and entertainment, and speculate on what the future might hold.Along the way, they discuss the importance of ethical considerations in developing and deploying AI systems, the potential for AI to exacerbate existing social and economic inequalities, and the need for greater transparency, accountability, and regulation in this rapidly evolving field.As they grapple with the fundamental question of how humanity can ensure a positive and sustainable relationship with AI, ChatGPT and his interlocutor offer readers a thought-provoking and nuanced exploration of one of the most pressing issues of our time.
Viruses in All Dimensions
Microorganisms, viruses, and computer programs encode all the information necessary to reproduce and spread themselves. Yet these mechanisms are amazingly similar in the animate world, in the world of viruses, and even in the world of technical systems. The book shows how great the parallels are between these various animate and inanimate replicating systems and what they are based on.The excursion also leads into the fascinating world of genetics, to the question of what defines life and into the programming of software that multiplies itself independently. Finally, the question is derived whether and to what extent such self-replicating technical systems can become as dangerous as infectious viruses in triggering pandemics, such as the Corona pandemic in 2020.
Introduction to Transfer Learning
Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a "student's" perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.
Computational Intelligence
This textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced third edition has been fully revised and expanded with new content on deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms. Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.
AI Ethics
This book introduces readers to critical ethical concerns in the development and use of artificial intelligence. Offering clear and accessible information on central concepts and debates in AI ethics, it explores how related problems are now forcing us to address fundamental, age-old questions about human life, value, and meaning. In addition, the book shows how foundational and theoretical issues relate to concrete controversies, with an emphasis on understanding how ethical questions play out in practice. All topics are explored in depth, with clear explanations of relevant debates in ethics and philosophy, drawing on both historical and current sources. Questions in AI ethics are explored in the context of related issues in technology, regulation, society, religion, and culture, to help readers gain a nuanced understanding of the scope of AI ethics within broader debates and concerns. Written with both students and educators in mind, the book is easy to use, with key terms clearly explained, and numerous exercises designed to stretch and challenge. It offers readers essential insights into the evolving field of AI ethics. Moreover, it presents a range of methods and strategies that can be used to analyse and understand ethical questions, which are illustrated throughout with case studies.
Intelligent Decision Support Systems
Presents the emergent interdisciplinary field of Intelligent Decision Support Systems (IDSS) Show how to analyze, to design, to implement, and to validate IDSS in complex systems Provide a comprehensive description of current issues in integration of different intelligent/numerical/statistical methods
Hands-On Computer Vision with Detectron2
Explore Detectron2 using cutting-edge models and learn all about implementing future computer vision applications in custom domainsPurchase of the print or Kindle book includes a free PDF eBookKey Features: - Learn how to tackle common computer vision tasks in modern businesses with Detectron2- Leverage Detectron2 performance tuning techniques to control the model's finest details- Deploy Detectron2 models into production and develop Detectron2 models for mobile devicesBook Description: Computer vision is a crucial component of many modern businesses, including automobiles, robotics, and manufacturing, and its market is growing rapidly. This book helps you explore Detectron2, Facebook's next-gen library providing cutting-edge detection and segmentation algorithms. It's used in research and practical projects at Facebook to support computer vision tasks, and its models can be exported to TorchScript or ONNX for deployment.The book provides you with step-by-step guidance on using existing models in Detectron2 for computer vision tasks (object detection, instance segmentation, key-point detection, semantic detection, and panoptic segmentation). You'll get to grips with the theories and visualizations of Detectron2's architecture and learn how each module in Detectron2 works. As you advance, you'll build your practical skills by working on two real-life projects (preparing data, training models, fine-tuning models, and deployments) for object detection and instance segmentation tasks using Detectron2. Finally, you'll deploy Detectron2 models into production and develop Detectron2 applications for mobile devices.By the end of this deep learning book, you'll have gained sound theoretical knowledge and useful hands-on skills to help you solve advanced computer vision tasks using Detectron2.What You Will Learn: - Build computer vision applications using existing models in Detectron2- Grasp the concepts underlying Detectron2's architecture and components- Develop real-life projects for object detection and object segmentation using Detectron2- Improve model accuracy using Detectron2's performance-tuning techniques- Deploy Detectron2 models into server environments with ease- Develop and deploy Detectron2 models into browser and mobile environmentsWho this book is for: If you are a deep learning application developer, researcher, or software developer with some prior knowledge about deep learning, this book is for you to get started and develop deep learning models for computer vision applications. Even if you are an expert in computer vision and curious about the features of Detectron2, or you would like to learn some cutting-edge deep learning design patterns, you will find this book helpful. Some HTML, Android, and C++ programming skills are advantageous if you want to deploy computer vision applications using these platforms.Table of Contents- An Introduction to Detectron2 and Computer Vision Tasks- Developing Computer Vision Applications Using Existing Detectron2 Models- Data Preparation for Object Detection Applications- The Architecture of the Object Detection Model in Detectron2- Training Custom Object Detection Models- Inspecting Training Results and Fine-Tuning Detectron2's Solver- Fine-Tuning Object Detection Models- Image Data Augmentation Techniques- Applying Train-Time and Test-Time Image Augmentations- Training Instance Segmentation Models- Fine-Tuning Instance Segmentation Models- Deploying Detectron2 Models into Server Environments- Deploying Detectron2 models into Browsers and Mobile Environments
Digital Freedom
In the present age of the digital era, the terms digitalization, emerging technologies, and social media have become buzzwords. Among all the innovations in our history, digital technology has advanced the fastest. With the freedom of digitalization, emerging technologies, and high-speed internet, computing devices may now work remotely. Every industry, including banking and finance, healthcare, agriculture, logistics, academia, government sectors, and businesses, has recognized the need for innovative digital technologies for their development, boosting efficiency and speed and cutting costs. Digitalization has also converted non-digital applications into digital ones to make things easier for people, at the same time that social media has an increasingly significant impact on human lives and industries. Consequently, the primary goal of this book is to explain to readers how newly emerging digital technologies and social media have significantly altered and aided in the growth of today's organizations and how the freedom of using these technologies has proved to be beneficial, particularly during the COVID-19 pandemic that has affected the entire world. This book demonstrates its argument by providing real-world cases from both developed and developing nations, particularly India. The book also investigates how digital transformation may help every industry and organization be more agile and efficient. Readers will learn about the main goals of digital initiatives that have been launched to create a digitally empowered society worldwide. In this book, the benefits and challenges of digitization, digital tools, and other technologies in diverse fields are also examined.
Machine Learning Governance for Managers
Machine Learning Governance for Managers provides readers with the knowledge to unlock insights from data and leverage AI solutions. In today's business landscape, most organizations face challenges in scaling and maintaining a sustainable machine learning model lifecycle. This book offers a comprehensive framework that covers business requirements, data generation and acquisition, modeling, model deployment, performance measurement, and management, providing a range of methodologies, technologies, and resources to assist data science managers in adopting data and AI-driven practices. Particular emphasis is given to ramping up a solution quickly, detailing skills and techniques to ensure the right things are measured and acted upon for reliable results and high performance. Readers will learn sustainable tools for implementing machine learning with existing IT and privacy policies, including versioning all models, creating documentation, monitoring models and their results, and assessing their causal business impact. By overcoming these challenges, bottom-line gains from AI investments can be realized. Organizations that implement all aspects of AI/ML model governance can achieve a high level of control and visibility over how models perform in production, leading to improved operational efficiency and a higher ROI on AI investments. Machine Learning Governance for Managers helps to effectively control model inputs and understand all the variables that may impact your results. Don't let challenges in machine learning hinder your organization's growth - unlock its potential with this essential guide.
How to Test a Time Machine
End-to-end solutions and options for test architecture and methodologies. Achieve better quality and faster projects in an enjoyable way taking your career to the next level.Key Features: - Explore the full test architecture spectrum- Discover a range of challenging automation applications with real-world scenarios- Learn with easy-to-follow start-up examples including DevOps for testing, AI, XR, and cloudBook Description: From simple websites to complex applications, delivering quality is crucial for achieving customer satisfaction. How to Test a Time Machine provides step-by-step explanations of essential concepts and practical examples to show you how you can leverage your company's test architecture from different points in the development life cycle.You'll begin by determining the most effective system for measuring and improving the delivery of quality applications for your company, and then learn about the test pyramid as you explore it in an innovative way. You'll also cover other testing topics, including cloud, AI, and VR for testing.Complete with techniques, patterns, tools, and exercises, this book will help you enhance your understanding of the testing process. Regardless of your current role within development, you can use this book as a guide to learn all about test architecture and automation and become an expert and advocate for quality assurance.By the end of this book, you'll be able to deliver high-quality applications by implementing the best practices and testing methodologies included in the book.What You Will Learn: - Identify quality maturity and processes to get your product to the next quality level- Learn how to think out of the box for testing- Learn about types of tests and how to apply them from a unique perspective- Understand how to apply different technologies into testing- Cool code exercises and tools that could be of use for practicing and polishing your testing skills- Own quality and use it for career growthWho this book is for: This book is for test owners, developers, managers, manual QAs, SDETS, team leads, and systems engineers who wish to get started or improve the current QA systems. Test owners looking for inspiration and out-of-the-box solutions for challenging issues will also find this book useful.Table of Contents- Introduction - Finding Your QA Level- The Secret Passages of the Test Pyramid - The Base of the Pyramid- The Secret Passages of the Test Pyramid -- The Middle of the Pyramid- The Secret Passages of the Test Pyramid - The Top of the Pyramid- Testing Automation Patterns- Continuous Testing - CI/CD and Other DevOps Concepts You Should Know- Mathematics and Algorithms in Testing- Artificial Intelligence is the New Intelligence- Having Your Head up in the Clouds- Traveling Across Realities- How to Test a Time Machine (and Other Hard-to-Test Applications)- Taking Your Testing to the Next Level- Appendix - Self-Assessment
Computer Vision on AWS
Scale up your Windows containers seamlessly on AWS powered by field-proven expertise and best practices on Amazon ECS, EKS, and FargatePurchase of the print or Kindle book includes a free PDF eBookKey Features: Learn how to quickly deploy and automate end-to-end CV pipelines on AWSImplement design principles to mitigate bias and scale production of CV workloadsWork with code examples to master CV concepts using AWS AI/ML servicesBook Description: Computer vision (CV) is a field of artificial intelligence that helps transform visual data into actionable insights to solve a wide range of business challenges. This book provides prescriptive guidance to anyone looking to learn how to approach CV problems for quickly building and deploying production-ready models.You'll begin by exploring the applications of CV and the features of Amazon Rekognition and Amazon Lookout for Vision. The book will then walk you through real-world use cases such as identity verification, real-time video analysis, content moderation, and detecting manufacturing defects that'll enable you to understand how to implement AWS AI/ML services. As you make progress, you'll also use Amazon SageMaker for data annotation, training, and deploying CV models. In the concluding chapters, you'll work with practical code examples, and discover best practices and design principles for scaling, reducing cost, improving the security posture, and mitigating bias of CV workloads.By the end of this AWS book, you'll be able to accelerate your business outcomes by building and implementing CV into your production environments with the help of AWS AI/ML services.What You Will Learn: Apply CV across industries, including e-commerce, logistics, and mediaBuild custom image classifiers with Amazon Rekognition Custom LabelsCreate automated end-to-end CV workflows on AWSDetect product defects on edge devices using Amazon Lookout for VisionBuild, deploy, and monitor CV models using Amazon SageMakerDiscover best practices for designing and evaluating CV workloadsDevelop an AI governance strategy across the entire machine learning life cycleWho this book is for: If you are a machine learning engineer or data scientist looking to discover best practices and learn how to build comprehensive CV solutions on AWS, this book is for you. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. A solid understanding of machine learning concepts and the Python programming language will also be beneficial.
