Artificial Intelligence
Harvard Business Review is the leading destination for smart management thinking. Through its flagship magazine, 12 international licensed editions, books from Harvard Business Review Press, and digital content and tools published on HBR.org, Harvard Business Review provides professionals around the world with rigorous insights and best practices to lead themselves and their organizations more effectively and to make a positive impact. Visit hbr.org. Follow @HarvardBiz on Twitter; find us on Facebook and LinkedIn.Author social media/website info: Twitter: @HarvardBiz; hbr.org; Facebook: @HBR; Instagram: @harvard_business_review
Artificial General Intelligence
This book constitutes the refereed proceedings of the 14th International Conference on Artificial General Intelligence, AGI 2021, held as a hybrid event in San Francisco, CA, USA, in October 2021.The 36 full papers presented in this book were carefully reviewed and selected from 50 submissions. The papers cover topics from foundations of AGI, to AGI approaches and AGI ethics, to the roles of systems biology, goal generation, and learning systems, and so much more.
Professional Cloud Architect Google Cloud Certification Guide - Second Edition
Become a Professional Cloud Architect by exploring the essential concepts, tools, and services in GCP and working through practice tests designed to help you take the exam confidentlyKey Features: Plan and design a GCP cloud solution architectureEnsure the security and reliability of your cloud solutions and operationsAssess your knowledge by taking mock tests with up-to-date exam questionsBook Description: Google Cloud Platform (GCP) is one of the industry leaders thanks to its array of services that can be leveraged by organizations to bring the best out of their infrastructure. This book is a comprehensive guide for learning methods to effectively utilize GCP services and help you become acquainted with the topics required to pass Google's Professional Cloud Architect certification exam.Following the Professional Cloud Architect's official exam syllabus, you'll first be introduced to the GCP. The book then covers the core services that GCP offers, such as computing and storage, and takes you through effective methods of scaling and automating your cloud infrastructure. As you progress through the chapters, you'll get to grips with containers and services and discover best practices related to the design and process. This revised second edition features new topics such as Cloud Run, Anthos, Data Fusion, Composer, and Data Catalog.By the end of this book, you'll have gained the knowledge required to take and pass the Google Cloud Certification - Professional Cloud Architect exam and become an expert in GCP services.What You Will Learn: Understand the benefits of being a Google Certified Professional Cloud ArchitectFind out how to enroll for the Professional Cloud Architect examMaster the compute options in GCPExplore security and networking options in GCPGet to grips with managing and monitoring your workloads in GCPUnderstand storage, big data, and machine learning servicesBecome familiar with exam scenarios and passing strategiesWho this book is for: If you are a cloud architect, cloud engineer, administrator, or any IT professional looking to learn how to implement Google Cloud services in your organization and become a GCP Certified Professional Cloud Architect, this book is for you. Basic knowledge of server infrastructure, including Linux and Windows Servers, is assumed. A solid understanding of network and storage will help you to make the most out of this book.
Coding
python codingWandering how to learn everything on Python Programming right from the beginning? The next few lines can tell you something! Learning Python is one of the 21st century specialties you can have right now. You know how to code with Python, you become one of the most relevant citizens of the computer age. You can access neural networks, interpret, understand, code and decode certain special languages of a computer. So in order to be relevant, you need a program like python. This field used to be restricted to Computer scientists, Engineers, Technicians and related fields originally. But today, everyone programs a computer and you can't afford not belonging to that class for long. Learning Python programming is your pathway to understanding neural networks and coding information into a computer. But learning the basic coding processes requires a lot of technicalities. What specialties do you stand to learn?Introduction to python machine.The process of neural networks and a brief overviewLearn coding with python in computer programmingOrganize data using effective pre-processing techniquesGet grips to a deeper textual and social media data C++ for beginners Do you need a capable and dedicated programming language that can cope with your requirements? The Ultimate Beginners Guide to Learn C++ Programming Step-by-Step, you have clear and concise information that will provide advantages such as: - How to set up a C++ development environment- The principles of programming that will get you started- Power of C++: operations, switches, loops and decision making- Getting started: syntax, data types, and variables- How to create custom functions in C++- The best practices for coding
Convergence of Artificial Intelligence and Blockchain Technologies, The: Challenges and Opportunities
This book covers the growing convergence between Blockchain and Artificial Intelligence for Big Data, Multi-Agent systems, the Internet of Things and 5G technologies. Using real case studies and project outcomes, it illustrates the intricate details of blockchain in these real-life scenarios. The contributions from this volume bring a state-of-the-art assessment of these rapidly evolving trends in a creative way and provide a key resource for all those involved in the study and practice of AI and Blockchain.
AWS All-in-one Security Guide
Learn to build robust security controls for the infrastructure, data, and applications in the AWSCloud.Key FeaturesTakes a comprehensive layered security approach that covers major use-cases.Covers key AWS security features leveraging the CLI and Management Console.Step-by-step instructions for all topics with graphical illustrations.Relevant code samples written in JavaScript (for Node.js runtime).DescriptionIf you're looking for a comprehensive guide to Amazon Web Services (AWS) security, this book is for you. With the help of this book, cloud professionals and the security team will learn how to protect their cloud infrastructure components and applications from external and internal threats.The book uses a comprehensive layered security approach to look into the relevant AWS services in each layer and discusses how to use them. It begins with an overview of the cloud's shared responsibility model and how to effectively use the AWS Identity and Access Management (IAM) service to configure identities and access controls for various services and components. The subsequent chapter covers AWS infrastructure security, data security, and AWS application layer security. Finally, the concluding chapters introduce the various logging, monitoring, and auditing services available in AWS, and the book ends with a chapter on AWS security best practices.By the end, as readers, you will gain the knowledge and skills necessary to make informed decisions and put in place security controls to create AWS application ecosystems that are highly secure.What you will learnLearn to create a layered security architecture and employ defense in depth.Master AWS IAM and protect APIs.Use AWS WAF, AWS Secrets Manager, and AWS Systems Manager Parameter Store.Learn to secure data in Amazon S3, EBS, DynamoDB, and RDS using AWS Key Management Service.Secure Amazon VPC, filter IPs, use Amazon Inspector, use ECR image scans, etc.Protect cloud infrastructure from DDoS attacks and use AWS Shield.Who this book is forThe book is intended for cloud architects and security professionals interested in delving deeper into the AWS cloud's security ecosystem and determining the optimal way to leverage AWS security features. Working knowledge of AWS and its core services is necessary.Table of Contents1. Introduction to Security in AWS2. Identity And Access Management3. Infrastructure Security4. Data Security5. Application Security6. Logging, Monitoring, And Auditing7. Security Best PracticesRead more
Practical AI for Healthcare Professionals
Practical AI for Healthcare Professionals Artificial Intelligence (AI) is a buzzword in the healthcare sphere today. However, notions of what AI actually is and how it works are often not discussed. Furthermore, information on AI implementation is often tailored towards seasoned programmers rather than the healthcare professional/beginner coder. This book gives an introduction to practical AI in the medical sphere, focusing on real-life clinical problems, how to solve them with actual code, and how to evaluate the efficacy of those solutions. You'll start by learning how to diagnose problems as ones that can and cannot be solved with AI. You'll then learn the basics of computer science algorithms, neural networks, and when each should be applied. Then you'll tackle the essential parts of basic Python programming relevant to data processing and making AI programs. The Tensorflow/Keras library along with Numpy and Scikit-Learn are covered as well. Once you've mastered those basic computer science and programming concepts, you can dive into projects with code, implementation details, and explanations. These projects give you the chance to explore using machine learning algorithms for issues such as predicting the probability of hospital admission from emergency room triage and patient demographic data. We will then use deep learning to determine whether patients have pneumonia using chest X-Ray images. The topics covered in this book not only encompass areas of the medical field where AI is already playing a major role, but also are engineered to cover as much as possible of AI that is relevant to medical diagnostics. Along the way, readers can expect to learn data processing, how to conceptualize problems that can be solved by AI, and how to program solutions to those problems. Physicians and other healthcare professionals who can master these skills will be able to lead AI-based research and diagnostic tool development, ultimately benefiting countless patients.
Connectionist Symbol Processing
Addressing the current tension within the artificial intelligence community between advocates of powerful symbolic representations that lack efficient learning procedures and advocates of relatively simple learning procedures that lack the ability to represent complex structures effectively.The six contributions in Connectionist Symbol Processing address the current tension within the artificial intelligence community between advocates of powerful symbolic representations that lack efficient learning procedures and advocates of relatively simple learning procedures that lack the ability to represent complex structures effectively. The authors seek to extend the representational power of connectionist networks without abandoning the automatic learning that makes these networks interesting.Aware of the huge gap that needs to be bridged, the authors intend their contributions to be viewed as exploratory steps in the direction of greater representational power for neural networks. If successful, this research could make it possible to combine robust general purpose learning procedures and inherent representations of artificial intelligence--a synthesis that could lead to new insights into both representation and learning.
Artificial Intelligence
The broad range of material included in these volumes suggests to the newcomer the nature of the field of artificial intelligence, while those with some background in AI will appreciate the detailed coverage of the work being done at MIT. The results presented are related to the underlying methodology. Each chapter is introduced by a short note outlining the scope of the problem begin taken up or placing it in its historical context.Contents, Volume II: Understanding Vision: Representing and Computing Visual Information; Visual Detection of Light Sources; Representing and Analyzing Surface Orientation; Registering Real Images Using Synthetic Images; Analyzing Curved Surfaces Using Reflectance Map Techniques; Analysis of Scenes from a Moving Viewpoint; Manipulation and Productivity Technology: Force Feedback in Precise Assembly Tasks; A Language for Automatic Mechanical Assembly; Kinematics, Statics, and Dynamics of Two-Dimensional Manipulators; Understanding Manipulator Control by Synthesizing Human Handwriting; Computer Design and Symbol Manipulation: The LISP Machine; Shallow Binding in LISP 1.5; Optimizing Allocation and Garbage Collection of Spaces; Compiler Optimization Based on Viewing LAMBDA as RENAME Plus GOTO; Control Structure as Patterns of Passing Messages.
Meta-Programming in Logic Programming
A comprehensive survey of the theory and applications of meta-programming, covering problems of representation and of soundness and correctness of interpreters, analysis and evaluation of meta-logic programs, and applications to sophisticated knowledge-based systems.Meta-programs, which treat other computer programs as data, include compilers, editors, simulators, debuggers, and program transformers. Because of the wide ranging applications, meta-programming has become a subject of considerable practical and theoretical interest. This book provides the first comprehensive view of topics in the theory and application of meta-programming, covering problems of representation and of soundness and correctness of interpreters, analysis and evaluation of meta-logic programs, and applications to sophisticated knowledge-based systems.Meta-Programming in Logic Programming is in the series Logic Programming Research Reports and Notes, edited by Ehud Shapiro.
Meta-Logics and Logic Programming
Investigating meta-programming within the logic programming paradigm, Meta-Logics and Logic Programming presents original research on an important extension of logic programming that makes it more amenable for knowledge representation and programming in general. The 12 contributions, many written especially for this book, explore the foundations, language design issues, and applications of meta-programming in logic programming. Meta-programming--the process of writing computer programs that can manipulate representations of other programs--has been key both in the foundations of computer science and in its practical developments. Examples of meta-programs include compilers, interpreters, program analyzers, and partial evaluators. The choice of logic programming as a basis for meta-programming offers several practical and theoretical advantages: among them, the possibility of tackling critical foundational problems of meta-programming within a strong theoretical framework, and the surprising ease of programming. The usual framework of logic programming (and more generally first-order logic), however, has to be modified and extended to formally deal with meta-programs, extensions the editors call meta-logics. Along with an exploration of meta-programming in logic programming, the definitions, formal properties, and use of these extensions constitute one of the book's main themes. The first part of the book, Foundations, focuses on the representation problem--how object programs are represented within meta-programs. The second part, Language Support for Meta-Logics, is concerned with language extensions that make meta-programming easier and more elegant. The third part, Meta-Logics for Knowledge Management, deals with the use of meta-logic for advanced knowledge representation purposes.
Eye Tracking and Visual Analytics
Visualization and visual analytics are powerful concepts for exploring data from various application domains. The endless number of possible parameters and the many ways to combine visual variables as well as algorithms and interaction techniques create lots of possibilities for building such techniques and tools.The major goal of those tools is to include the human users with their tasks at hand, their hypotheses, and research questions to provide ways to find solutions to their problems or at least to hint them in a certain direction to come closer to a problem solution. However, due to the sheer number of design variations, it is unclear which technique is suitable for those tasks at hand, requiring some kind of user evaluation to figure out how the human users perform while solving their tasks.The technology of eye tracking has existed for a long time; however, it has only recently been applied to visualization and visual analytics as a means to provide insights to the users' visual attention behavior. This generates another kind of dataset that has a spatio-temporal nature and hence demands for advanced data science and visual analytics concepts to find insights into the recorded eye movement data, either as a post process or even in real-time. This book describes aspects from the interdisciplinary field of visual analytics, but also discusses more general approaches from the field of visualization as well as algorithms and data handling. A major part of the book covers research on those aspects under the light and perspective of eye tracking, building synergy effects between both fields - eye tracking and visual analytics - in both directions, i.e. eye tracking applied to visual analytics and visual analytics applied to eye tracking data.Technical topics discussed in the book include: - Visualization; - Visual Analytics; - User Evaluation; - Eye Tracking; - Eye Tracking Data Analytics;Eye Tracking and Visual Analytics includes more than 500 references from the fields of visualization, visual analytics, user evaluation, eye tracking, and data science, all fields which have their roots in computer science.Eye Tracking and Visual Analytics is written for researchers in both academia and industry, particularly newcomers starting their PhD, but also for PostDocs and professionals with a longer research history in one or more of the covered research fields. Moreover, it can be used to get an overview about one or more of the involved fields and to understand the interface and synergy effects between all of those fields. The book might even be used for teaching lectures in the fields of information visualization, visual analytics, and/or eye tracking.
The Golden Age of KNOWLEDGE
The human history have been devided into ages according to the tools that were used and the important social and political events that had an effect on human history. Now for the first time in the history, it is named according to the time and space that's lived in.With this book, the knowledge limits of higher dimension only one thought beyond us have been overcome, the mental lock of the visible world has been unlocked and the awaited transition has begun! Welcome to The Golden of Knowledge Of the Dimension / Where Time and Space DO NOT EXIST...FOREWORDOne can only achieve to end something if he destroys its philosophy. One way to avoid and put an end fighting and wars on a holistic scale is devaluing the means that we fight for; - To have a contact with you - Receive the first 'Nobel Peace Prize' which serves not only the peace amongst humans but peace amongst every being in the universe whether animate or inanimate - And of course for 'Him'. We are living in a universe where even a minor detail can create a crucial level of awareness or an ordinary thought can change everything. Please contribute with your ideas, share your thoughts even if it's about a very small detail, if you are one of those who think they would write, tell, express some-thing differently than I did. Be one of those who write this book for the new edition. The personal successes and failures as well as the happiness and the unhappiness that we experienced have helped us spe-cialize in different areas of the whole. While moving to a phase of social development from a phase of personal devel-opment and reckoning what hasn't manifested yet, let us be amongst those who write, explain and design the future with the new answers and questions we will find. Let us be one of those who think and stimulate others to think. One has to start by questioning the time and space he is living in, if he is to understand that he is in a dream...
Data Science Ethics
Data science ethics is all about what is right and wrong when conducting data science. Data science has so far been primarily used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. While data scientists and business managers are not inherently unethical, they are not trained to weigh the ethical considerations that come from their work - iData Science Ethics/i addresses this increasingly significant gap and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques. Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data.
Data Science Ethics
Data science ethics is all about what is right and wrong when conducting data science. Data science has so far been primarily used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. While data scientists and business managers are not inherently unethical, they are not trained to weigh the ethical considerations that come from their work - iData Science Ethics/i addresses this increasingly significant gap and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques. Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data.
Cloud Audit Toolkit for Financial Regulators
This toolkit is designed to assist and accelerate the uptake of cloud computing technologies and digital tools to improve the efficiency and efficacy of financial regulators' work processes in ADB's developing member countries. Drawing on existing practices observed by leading regulators from across the globe, the toolkit provides a comprehensive framework for improving supervisory work processes. It also includes a checklist that will help regulators to conduct an initial review of their existing oversight mechanisms.
Information and Communication Technologies for Development
This book constitutes the refereed proceedings of the 16th IFIP WG 9.4 International Conference on Social Implications of Computers in Developing Countries, ICT4D 2020, which was supposed to be held in Salford, UK, in June 2020, but was held virtually instead due to the COVID-19 pandemic. The 18 revised full papers presented were carefully reviewed and selected from 29 submissions. The papers present a wide range of perspectives and disciplines including (but not limited to) public administration, entrepreneurship, business administration, information technology for development, information management systems, organization studies, philosophy, and management. They are organized in the following topical sections: digital platforms and gig economy; education and health; inclusion and participation; and business innovation and data privacy.
Is AI Good for the Planet?
Artificial intelligence (AI) is presented as a solution to the greatest challenges of our time, from global pandemics and chronic diseases to cybersecurity threats and the climate crisis. But AI also contributes to the climate crisis by running on technology that depletes scarce resources and by relying on data centres that demand excessive energy use. Is AI Good for the Planet? brings the climate crisis to the centre of debates around AI, exposing its environmental costs and forcing us to reconsider our understanding of the technology. It reveals why we should no longer ignore the environmental problems generated by AI. Embracing a green agenda for AI that puts the climate crisis at centre stage is our urgent priority. Engaging and passionately written, this book is essential reading for scholars and students of AI, environmental studies, politics, and media studies and for anyone interested in the connections between technology and the environment.
Life and Death Design
"Katie Swindler does a brilliant job of breaking down our stress response, with vivid stories that demonstrate how the systems we create can help or hinder at critical times."-- Carolyn Chandler, coauthor, A Project Guide to UX Design and Adventures in Experience DesignEmergencies--landing a malfunctioning plane, resuscitating a heart attack victim, or avoiding a head-on car crash--all require split-second decisions that can mean life or death. Fortunately, designers of life-saving products have leveraged research and brain science to help users reduce panic and harness their best instincts.Life and Death Design brings these techniques to everyday designers who want to help their users think clearly and act safely.
Practical Explainable AI Using Python
Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black-box models to boost the adaptability, interpretability, and explainability of the decisions made by AI algorithms using frameworks such as Python XAI libraries, TensorFlow 2.0+, Keras, and custom frameworks using Python wrappers.You'll begin with an introduction to model explainability and interpretability basics, ethical consideration, and biases in predictions generated by AI models. Next, you'll look at methods and systems to interpret linear, non-linear, and time-series models used in AI. The book will also cover topics ranging from interpreting to understanding how an AI algorithm makes a decision Further, you will learn the most complex ensemble models, explainability, and interpretability using frameworks such as Lime, SHAP, Skater, ELI5, etc. Moving forward, youwill be introduced to model explainability for unstructured data, classification problems, and natural language processing-related tasks. Additionally, the book looks at counterfactual explanations for AI models. Practical Explainable AI Using Python shines the light on deep learning models, rule-based expert systems, and computer vision tasks using various XAI frameworks.What You'll LearnReview the different ways of making an AI model interpretable and explainableExamine the biasness and good ethical practices of AI modelsQuantify, visualize, and estimate reliability of AI modelsDesign frameworks to unbox the black-box modelsAssess the fairness of AI modelsUnderstand the building blocks of trust in AI modelsIncrease the level of AI adoptionWho This Book Is ForAI engineers, data scientists, and software developers involved in driving AI projects/ AI products.
Managing AI in the Enterprise
Delivering AI projects and building an AI organization are two big challenges for enterprises. They determine whether companies succeed or fail in establishing AI and integrating AI into their digital transformation. This book addresses both challenges by bringing together organizational and service design concepts, project management, and testing and quality assurance. It covers crucial, often-overlooked topics such as MLOps, IT risk, security and compliance, and AI ethics. In particular, the book shows how to shape AI projects and the capabilities of an AI line organization in an enterprise. It elaborates critical deliverables and milestones, helping you turn your vision into a corporate reality by efficiently managing and setting goals for data scientists, data engineers, and other IT specialists. For those new to AI or AI in an enterprise setting you will find this book a systematic introduction to the field. You will get the necessary know-how to collaborate with and lead AI specialists and guide them to success. Time-pressured readers will benefit from self-contained sections explaining key topics and providing illustrations for fostering discussions in their next team, project, or management meeting. Reading this book helps you to better sell the business benefits from your AI initiatives and build your skills around scoping and delivering AI projects. You will be better able to work through critical aspects such as quality assurance, security, and ethics when building AI solutions in your organization. What You Will LearnClarify the benefits of your AI initiatives and sell them to senior managersScope and manage AI projects in your organizationSet up quality assurance and testing for AI models and their integration in complex software solutionsShape and manage an AI delivery organization, thereby mastering ML Ops Understand and formulate requirements for the underlying data management infrastructureHandle AI-related IT security, compliance, and risk topics and understand relevant AI ethics aspects Who This Book Is ForExperienced IT managers managing data scientists or who want to get involved in managing AI projects, data scientists and other tech professionals who want to progress toward taking on leadership roles in their organization's AI initiatives and who aim to structure AI projects and AI organizations, any line manager and project manager involved in AI projects or in collaborating with AI teams
Designs on Transcendence
Despite the vast number of people who use technology as a part of their spiritual and transcendental practice, there is little research on the subject of digital transcendence in studies of Human Computer Interaction (HCI). This monograph reviews the work that HCI has produced in this area but also draws on related research in psychology, philosophy, sociology, anthropology, digital religion, psychopharmacology, and neuroscience. While there are a wide range of perspectives within the literature, transcendent experiences (TXs) are similar across religious and cultural backgrounds but interpretations vary according to world view. Recurring terms describing these experiences are: ineffable, intense, ephemeral, paradoxical, sacred, unity, epiphany, altered perception of time and space, ecstasy, tranquility, gratitude, awe, and reverence. Studies also record benefits of TXs such as substance use recovery and improved mental health. Transcendence and spirituality are deeply subjective experiences and there are many aspects of this topic that academic writing cannot easily approach. For this reason, the authors have combined a traditional academic review with design fiction. They explore the themes in the literature through an illustrated design fiction depicting a near future conference on TX research. This is an extended and illustrated speculation around brain computer interfaces that might evoke TXs. The monograph ends with a manifesto calling for a radically interdisciplinary field that would bridge cultural divides and move beyond models of health and wellbeing to establish new forums and venues for TX research.
VR
Vic Rostrun has had a tough life since his parents, world-famous archaeologists, went missing whilst on an expedition in the deep dark rain forests of Central America. But all this changes when Vic is given an amazing new computer by his 'larger than life' uncle. Following a freak lightning strike, the computer is mysteriously transformed and Vic gains access to virtual reality - a world that exists within a microchip inside his computer. Now part detective, part explorer, Vic carries out some thrilling virtual visits and eventually discovers that his parents are being held captive by an evil Mayan King in a secret underground city. Given what seems like an impossible quest by the King as the only means of rescuing them, can virtual reality enable Vic to undertake the ultimate daring mission to bring them home?
Innovating with Augmented Reality
Augmented Reality (AR) has many advantages that include increased engagement and interaction as well as enhanced innovation and responsiveness. AR technology has applications in almost all domains such as medical training, retail, repair and maintenance of complex equipment, interior design in architecture and construction, business logistics, tourism, and classroom education. Innovating with Augmented Reality: Applications in Education and Industry explains the concepts behind AR, explores some of its application areas, and gives an in-depth look at how this technology aligns with Education 4.0. Due to the rapid advancements in technology, future education systems must prepare students to work with the latest technologies by enabling them to learn virtually in augmented ways in varied platforms. By providing an illusion of physical objects, which takes the students to a new world of imagination, AR and Virtual Reality (VR) create virtual and interactive environments for better learning and understanding. AR applications in education are covered in four chapters of this book, including a chapter on how gamification can be made use of in the teaching and learning process. The book also covers other application areas of AR and VR. One such application area is the food and beverage industry with case studies on virtual 3D food, employee training, product-customer interaction, restaurant entertainment, restaurant tours, and product packaging. The application of AR in the healthcare sector, medical education, and related devices and software are examined in the book's final chapter. The book also provides an overview of the game development software, Unity, a real-time development platform for 2D and 3D AR and VR, as well as the software tools and techniques used in developing AR-based apps.
Machine Learning with PySpark
Master the new features in PySpark 3.1 to develop data-driven, intelligent applications. This updated edition covers topics ranging from building scalable machine learning models, to natural language processing, to recommender systems. Machine Learning with PySpark, Second Edition begins with the fundamentals of Apache Spark, including the latest updates to the framework. Next, you will learn the full spectrum of traditional machine learning algorithm implementations, along with natural language processing and recommender systems. You'll gain familiarity with the critical process of selecting machine learning algorithms, data ingestion, and data processing to solve business problems. You'll see a demonstration of how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forests. You'll also learn how to automate the steps using Spark pipelines, followed by unsupervised models such as K-means and hierarchical clustering. A section on Natural Language Processing (NLP) covers text processing, text mining, and embeddings for classification. This new edition also introduces Koalas in Spark and how to automate data workflow using Airflow and PySpark's latest ML library. After completing this book, you will understand how to use PySpark's machine learning library to build and train various machine learning models, along with related components such as data ingestion, processing and visualization to develop data-driven intelligent applications What you will learn: Build a spectrum of supervised and unsupervised machine learning algorithmsUse PySpark's machine learning library to implement machine learning and recommender systems Leverage the new features in PySpark's machine learning libraryUnderstand data processing using Koalas in Spark Handle issues around feature engineering, class balance, bias andvariance, and cross validation to build optimally fit models Who This Book Is For Data science and machine learning professionals.
Voice Technologies for Speech Reconstruction and Enhancement
The book explores new ways to reconstruct and enhance speech that is compromised by various neuro-motor disorders - collectively known as "dysarthria." The authors address some of the extant lacunae in speech research of dysarthric conditions: they show how new methods can improve speaker recognition when speech is impaired due to developmental or acquired pathologies; they present a novel multi-dimensional approach to help the speech system both assess dysarthric speech and to perform intelligibility improvement of the impaired speech; they display well-performing software solutions for developmental and acquired speech impairments, and for vocal injuries; and they examine non-acoustic signals and muted nonverbal sounds in relation to audible speech conversion.
Machine Learning Applications
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
Designing React Hooks the Right Way
Get to grips with React Hooks and design your own custom Hook to manage application states for making better decisions in site architectureKey Features: Get to grips with Hooks' design and understand each built-in Hook's pitfalls with examplesDiscover how to turn your existing code into a reusable Hook via code refactoringExplore design solutions to identify and solve site performance issues involving HooksBook Description: React hook creates a unique solution for using states in function components to orchestrate UI communication. They provide you with an easy interface to write custom data management solutions with low development and maintenance costs. Understanding how Hooks are designed enables you to use them more effectively, and this book helps you to do just that.This book starts with a custom-crafted solution to reveal why Hooks are needed in the first place. You will learn about the React engine and discover how each built-in Hook can manage a persistent value by hooking into it. You will walk through the design and implementation of each hook with code so that you gain a solid understanding. Finally, you'll get to grips with each Hook's pitfalls and find out how to effectively overcome them.By the end of this React book, you'll have gained the confidence to build and write Hooks for developing functional and efficient web applications at scale.What You Will Learn: Create your own hooks to suit your state management requirementDetect the current window size of your website using useEffectDebounce an action to improve user interface (UI) performance using useMemoEstablish a global site configuration using useContextAvoid hard-to-find application memory leaks using useRefDesign a simple and effective API data layer using custom HooksWho this book is for: This book is for web developers who are looking for a consistent and efficient approach for applying application states with Hooks. Basic knowledge of React will help you to get the most out of this book.
Data Science and Computational Intelligence
This book constitutes revised and selected papers from the Sixteenth International Conference on Information Processing, ICInPro 2021, held in Bangaluru, India in October 2021. The 33 full and 9 short papers presented in this volume were carefully reviewed and selected from a total of 177 submissions. The papers are organized in the following thematic blocks: ​Computing & Network Security; Data Science; Intelligence & IoT.
Neural Information Processing
The two-volume set CCIS 1516 and 1517 constitutes thoroughly refereed short papers presented at the 28th International Conference on Neural Information Processing, ICONIP 2021, held in Sanur, Bali, Indonesia, in December 2021.* The volume also presents papers from the workshop on Artificial Intelligence and Cyber Security, held during the ICONIP 2021. The 176 short and workshop papers presented in this volume were carefully reviewed and selected for publication out of 1093 submissions. The papers are organized in topical sections as follows: theory and algorithms; AI and cybersecurity; cognitive neurosciences; human centred computing; advances in deep and shallow machine learning algorithms for biomedical data and imaging; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; applications.* The conference was held virtually due to the COVID-19 pandemic.
Neural Information Processing
The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
Natural Language Processing Projects
Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libraries and algorithms to build end-to-end NLP projects. The book starts with an overview of natural language processing (NLP) and artificial intelligence to provide a quick refresher on algorithms. Next, it covers end-to-end NLP projects beginning with traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. From there, it delves into e-commerce related projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. Moving forward, it explains how to build systems to find similar sentences using contextual embedding, summarizing huge documents using recurrent neural networks (RNN), automatic word suggestion using long short-term memory networks (LSTM), and how to build a chatbot using transfer learning. It concludes with an exploration of next-generation AI and algorithms in the research space. By the end of this book, you will have the knowledge needed to solve various business problems using NLP techniques. What You Will LearnImplement full-fledged intelligent NLP applications with PythonTranslate real-world business problem on text data with NLP techniquesLeverage machine learning and deep learning techniques to perform smart language processingGain hands-on experience implementing end-to-end search engine information retrieval, text summarization, chatbots, text generation, document clustering and product classification, and more Who This Book Is ForData scientists, machine learning engineers, and deep learning professionals looking to build natural language applications using Python
Towards the Automatization of Cranial Implant Design in Cranioplasty II
This book constitutes the Second Automatization of Cranial Implant Design in Cranioplasty Challenge, AutoImplant 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September, 2021. The challenge took place virtually due to the COVID-19 pandemic. The 7 papers are presented together with one invited paper, one qualitative evaluation criteria from neurosurgeons and a dataset descriptor. This challenge aims to provide more affordable, faster, and more patient-friendly solutions to the design and manufacturing of medical implants, including cranial implants, which is needed in order to repair a defective skull from a brain tumor surgery or trauma. The presented solutions can serve as a good benchmark for future publications regarding 3D volumetric shape learning and cranial implant design.
Kubernetes - An Enterprise Guide - Second Edition
Master core Kubernetes concepts important to enterprises from security, policy, and management point-of-view. Learn to deploy a service mesh using Istio, build a CI/CD platform, and provide enterprise security to your clusters.Key Features: Extensively revised edition to cover the latest updates and new releases along with two new chapters to introduce IstioGet a firm command of Kubernetes from a dual perspective of an admin as well as a developerUnderstand advanced topics including load balancing, externalDNS, global load balancing, authentication integration, policy, security, auditing, backup, Istio and CI/CDBook Description: Kubernetes has taken the world by storm, becoming the standard infrastructure for DevOps teams to develop, test, and run applications. With significant updates in each chapter, this revised edition will help you acquire the knowledge and tools required to integrate Kubernetes clusters in an enterprise environment.The book introduces you to Docker and Kubernetes fundamentals, including a review of basic Kubernetes objects. You'll get to grips with containerization and understand its core functionalities such as creating ephemeral multinode clusters using KinD. The book has replaced PodSecurityPolicies (PSP) with OPA/Gatekeeper for PSP-like enforcement. You'll integrate your container into a cloud platform and tools including MetalLB, externalDNS, OpenID connect (OIDC), Open Policy Agent (OPA), Falco, and Velero. After learning to deploy your core cluster, you'll learn how to deploy Istio and how to deploy both monolithic applications and microservices into your service mesh. Finally, you will discover how to deploy an entire GitOps platform to Kubernetes using continuous integration and continuous delivery (CI/CD).What You Will Learn: Create a multinode Kubernetes cluster using KinDImplement Ingress, MetalLB, ExternalDNS, and the new sandbox project, K8GBConfigure a cluster OIDC and impersonationDeploy a monolithic application in Istio service meshMap enterprise authorization to KubernetesSecure clusters using OPA and GateKeeperEnhance auditing using Falco and ECKBack up your workload for disaster recovery and cluster migrationDeploy to a GitOps platform using Tekton, GitLab, and ArgoCDWho this book is for: This book is for anyone interested in DevOps, containerization, and going beyond basic Kubernetes cluster deployments. DevOps engineers, developers, and system administrators looking to enhance their IT career paths will also find this book helpful.Although some prior experience with Docker and Kubernetes is recommended, this book includes a Kubernetes bootcamp that provides a description of Kubernetes objects to help you if you are new to the topic or need a refresher.
Automated Testing in Microsoft Dynamics 365 Business Central - Second Edition
Learn how to write automated tests for Dynamics 365 Business Central and discover how you can implement them in your daily workKey Features: Leverage automated testing to advance over traditional manual testing methodsWrite, design, and implement automated testsExplore various testing frameworks and tools compatible with Microsoft Dynamics 365 Business CentralBook Description: Dynamics 365 Business Central is a cloud-based SaaS ERP proposition from Microsoft. With development practices becoming more formal, implementing changes or new features is not as simple as it used to be back when Dynamics 365 Business Central was called Navigator, Navision Financials, or Microsoft Business Solutions-Navision, and the call for test automation is increasing.This book will show you how to leverage the testing tools available in Dynamics 365 Business Central to perform automated testing. Starting with a quick introduction to automated testing and test-driven development (TDD), you'll get an overview of test automation in Dynamics 365 Business Central. You'll then learn how to design and build automated tests and explore methods to progress from requirements to application and testing code. Next, you'll find out how you can incorporate your own as well as Microsoft tests into your development practice. With the addition of three new chapters, this second edition covers in detail how to construct complex scenarios, write testable code, and test processes with incoming and outgoing calls.By the end of this book, you'll be able to write your own automated tests for Microsoft Business Central.What You Will Learn: Understand the why and when of automated testingDiscover how test-driven development can help to improve automated testingExplore the six pillars of the Testability Framework of Business CentralDesign and write automated tests for Business CentralMake use of standard automated tests and their helper librariesUnderstand the challenges in testing features that interact with the external worldIntegrate automated tests into your development practiceWho this book is for: This book is for consultants, testers, developers, and development managers working with Microsoft Dynamics 365 Business Central. Functional as well as technical development teams will find this book on automated testing techniques useful.
Neural Information Processing
The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
Neural Information Processing
The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
Neural Information Processing
The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
The Future of Digital Work: The Challenge of Inequality
This book constitutes the refereed proceedings of the IFIP WG 8.2, 9.1, 9.4 Joint Working Conference on the Future of Digital Work: The Challenge of Inequality, IFIPJWC 2020, which was supposed to be held in Hyderabad, India, in December 2020, but was held virtually due to the COVID-19 pandemic. This conference was organized for IFIP's 60th anniversary and to commemorate its mission to "achieve worldwide professional and socially responsible development and application of ICTs."The 22 full papers presented together with an introduction and two keynotes were carefully reviewed and selected from 29 submissions. They are organized in topics on: innovation and entrepreneurship; the social significance of digital platforms; transforming healthcare; and the dark side of digitalization.
Advances in Visual Computing
This two-volume set of LNCS 13017 and 13018 constitutes the refereed proceedings of the 16th International Symposium on Visual Computing, ISVC 2021, which was held in October 2021. The symposium took place virtually instead due to the COVID-19 pandemic. The 48 papers presented in these volumes were carefully reviewed and selected from 135 submissions. The papers are organized into the following topical sections: Part I: deep learning; computer graphics; segmentation; visualization; applications; 3D vision; virtual reality; motion and tracking; object detection and recognition. Part II: ST: medical image analysis; pattern recognition; video analysis and event recognition; posters.
Optimization, Learning Algorithms and Applications
This book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragan癟a, Portugal, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 39 full papers and 13 short papers were thoroughly reviewed and selected from 134 submissions. They are organized in the topical sections on optimization theory; robotics; measurements with the internet of things; optimization in control systems design; deep learning; data visualization and virtual reality; health informatics; data analysis; trends in engineering education.
Human-Computer Interaction
This book constitutes the thoroughly refereed proceedings of the 7th Iberoamerican Workshop on Human-Computer Interaction, HCI-Collab 2021, held in Sao Paulo, Brazil, in September 2021.*The 15 full and 4 short papers presented in this volume were carefully reviewed and selected from 68 submissions. The papers deal with topics such as emotional interfaces, usability, video games, computational thinking, collaborative systems, IoT, software engineering, ICT in education, augmented and mixed virtual reality for education, gamification, emotional Interfaces, adaptive instruction systems, accessibility, use of video games in education, artificial Intelligence in HCI, among others.*The workshop was held virtually due to the COVID-19 pandemic.
Exam Ref Ai-900 Microsoft Azure AI Fundamentals
Prepare for Microsoft Exam AI-900 and help demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) workloads, and how they can be implemented with Azure AI. Designed for business stakeholders, new and existing IT professionals, consultants, and students, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure AI Fundamentals level. Focus on the expertise measured by these objectives: - Describe AI workloads and considerations - Describe fundamental principles of machine learning on Azure - Describe features of computer vision workloads on Azure - Describe features of Natural Language Processing (NLP) workloads on Azure - Describe features of conversational AI workloads on Azure This Microsoft Exam Ref: - Organizes its coverage by exam objectives - Features strategic, what-if scenarios to challenge you - Assumes you are a business user, stakeholder, technical professional, or student who wants to become familiar with Azure AI; requires no data science or software engineering experience. About the Exam Exam AI-900 focuses on knowledge needed to identify features of common AI workloads and guiding principles for responsible AI; identify common ML types; describe core ML concepts; identify core tasks in creating an ML solution; describe capabilities of no-code ML with Azure Machine Learning Studio; identify common types of computer vision solutions; identify Azure tools and services for computer vision tasks; identify features of common NLP workload scenarios; identify Azure tools and services for NLP workloads; and identify common use cases and Azure services for conversational Al. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure AI Fundamentals certification, demonstrating your knowledge of common ML and AI workloads and how to implement them on Azure. With this certification, you can move on to earn more advanced role-based certifications, including Microsoft Certified: Azure AI Engineer Associate or Azure Data Scientist Associate. See full details at: microsoft.com/learn
Deceptive AI
This book constitutes selected papers presented at the First International Workshop on Deceptive AI, DeceptECAI 2020, held in conjunction with the 24th European Conference on Artificial Intelligence, ECAI 2020, in Santiago de Compostela, Spain, in August 2020, and Second International Workshop on Deceptive AI, DeceptAI 2021, held in conjunction with the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021, in Montreal, Canada, in August 2021. Due to the COVID-19 pandemic both conferences were held in a virtual mode. The 12 papers presented were thoroughly reviewed and selected from the 16 submissions. They present recent developments in the growing area of research in the interface between deception and AI.
Situated Design Methods
A handbook of situated design methods, with analyses and cases that range from designing study processes to understanding customer experiences to developing interactive installations. All design is situated--carried out from an embedded position. Design involves many participants and encompasses a range of interactions and interdependencies among designers, designs, design methods, and users. Design is also multidisciplinary, extending beyond the traditional design professions into such domains as health, culture, education, and transportation. This book presents eighteen situated design methods, offering cases and analyses of projects that range from designing interactive installations, urban spaces, and environmental systems to understanding customer experiences. Each chapter presents a different method, combining theoretical, methodological, and empirical discussions with accounts of actual experiences. The book describes methods for defining and organizing a design project, organizing collaborative processes, creating aesthetic experiences, and incorporating sustainability into processes and projects. The diverse and multidisciplinary methods presented include a problem- and project-based approach to design studies; a "Wheel of Rituals" intended to promote creativity; a pragmatist method for situated experience design that derives from empirical studies of film production and performance design; and ways to transfer design methods in a situated manner. The book will be an important resource for researchers, students, and practitioners of interdisciplinary design.
Advanced Analytics and Learning on Temporal Data
This book constitutes the refereed proceedings of the 6th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2021, held during September 13-17, 2021. The workshop was planned to take place in Bilbao, Spain, but was held virtually due to the COVID-19 pandemic. The 12 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on the following topics: Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Multivariate Time Series Co-clustering; Efficient Event Detection; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Cluster-based Forecasting; Explanation Methods for Time Series Classification; Multimodal Meta-Learning for Time Series Regression; and Multivariate Time Series Anomaly Detection.
Deep Learning on Graphs
Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to advanced settings; Part 3 presents the most typical applications including natural language processing, computer vision, data mining, biochemistry and healthcare; and Part 4 describes advances of methods and applications that tend to be important and promising for future research. The book is self-contained, making it accessible to a broader range of readers including (1) senior undergraduate and graduate students; (2) practitioners and project managers who want to adopt graph neural networks into their products and platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.
