Mathematical and Computational Modelling of Covid-19 Transmission
This book addresses issues during the Covid phase and post-Covid phase through mathematical modeling.
Neural Networks and Deep Learning
This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail. The chapters of this book span three categories: The basics of neural networks: The backpropagation algorithm is discussed in Chapter 2.Many traditional machine learning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 4 and 5. Chapters 6 and 7 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 8, 9, and 10 discuss recurrent neural networks, convolutional neural networks, and graph neural networks. Several advanced topics like deep reinforcement learning, attention mechanisms, transformer networks, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 11 and 12. The textbook is written for graduate students and upper under graduate level students. Researchers and practitioners working within this related field will want to purchase this as well.Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.The second edition is substantially reorganized and expanded with separate chapters on backpropagation and graph neural networks. Many chapters have been significantly revised over the first edition.Greater focus is placed on modern deep learning ideas such as attention mechanisms, transformers, and pre-trained language models.
Data Engineering with dbt
Use easy-to-apply patterns in SQL and Python to adopt modern analytics engineering to build agile platforms with dbt that are well-tested and simple to extend and runPurchase of the print or Kindle book includes a free PDF eBookKey Features- Build a solid dbt base and learn data modeling and the modern data stack to become an analytics engineer- Build automated and reliable pipelines to deploy, test, run, and monitor ELTs with dbt Cloud- Guided dbt + Snowflake project to build a pattern-based architecture that delivers reliable datasetsBook Descriptiondbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps. This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You'll find out how to leverage data modeling, data quality, master data management, and more to build a simple-to-understand and future-proof solution. As you advance, you'll explore the modern data stack, understand how data-related careers are changing, and see how dbt enables this transition into the emerging role of an analytics engineer. The chapters help you build a sample project using the free version of dbt Cloud, Snowflake, and GitHub to create a professional DevOps setup with continuous integration, automated deployment, ELT run, scheduling, and monitoring, solving practical cases you encounter in your daily work. By the end of this dbt book, you'll be able to build an end-to-end pragmatic data platform by ingesting data exported from your source systems, coding the needed transformations, including master data and the desired business rules, and building well-formed dimensional models or wide tables that'll enable you to build reports with the BI tool of your choice.What you will learn- Create a dbt Cloud account and understand the ELT workflow- Combine Snowflake and dbt for building modern data engineering pipelines- Use SQL to transform raw data into usable data, and test its accuracy- Write dbt macros and use Jinja to apply software engineering principles- Test data and transformations to ensure reliability and data quality- Build a lightweight pragmatic data platform using proven patterns- Write easy-to-maintain idempotent code using dbt materializationWho this book is forThis book is for data engineers, analytics engineers, BI professionals, and data analysts who want to learn how to build simple, futureproof, and maintainable data platforms in an agile way. Project managers, data team managers, and decision makers looking to understand the importance of building a data platform and foster a culture of high-performing data teams will also find this book useful. Basic knowledge of SQL and data modeling will help you get the most out of the many layers of this book. The book also includes primers on many data-related subjects to help juniors get started.Table of Contents- Basics of SQL to transform data- Setting up your dbt Cloud development environment- Data modelling for data engineering- Analytics Engineering as the New Core of Data Engineering- Transforming data with dbt- Writing Maintainable Code- Working with Dimensional Data- Delivering Consistency In Your Code- Delivering Reliability In Your Data- Agile development- Collaboration- Deployment, Execution and Documentation Automation- Moving beyond basics- Enhancing Software Quality- Patterns for frequent use cases
Exchange 2000 .Net Server Black Book
Exchange 2000. NET Server Black Book is a comprehensive reference to administering, configuring, and troubleshooting Exchange 2000. Written in the popular Black Book problem-solving format, the book teaches you how to utilize the new features of Exchange 2000 and SMTP. It covers migrations issues and planning for: design and integration, site topology and organization, corporate and user's needs, Exchange Service selection, and disaster recovery.
Power BI Machine Learning and OpenAI
Unleash the full potential of Power BI with the integration of AI and machine learning techniques using OpenAIPurchase of the print or Kindle book includes a free PDF eBookKey Features: Take flight with Power BI machine learning and OpenAI using hands-on examples from the FAA airline dataUnlock the full potential of Power BI for advanced analytics using OpenAIDesign stunning data presentations, seamless integration of machine learning tools and technologies with OpenAIBook Description: Microsoft Power BI is the ultimate solution for businesses looking to make data-driven decisions and unlock the full potential of their data. Unleashing Your Data with Power BI Machine Learning and OpenAI is designed for data scientists and BI professionals seeking to improve their existing solutions and workloads using AI.The book explains the intricacies of the subject by using a workshop-style data story for data ingestion, data modeling, analytics, and predictive analytics with Power BI machine learning. Along the way, you'll learn about AI features, AI visuals, R/Python integration, and OpenAI integration.The workshop-style content allows you to practice all your learnings in real-life challenges and gain hands-on experience. Additionally, you'll gain an understanding of AI/ML, step by step, with replicable examples and references. From enhancing data visualizations to building SaaS Power BI ML models, and integrating Azure OpenAI, this book will help you unlock new capabilities in Power BI.By the end of this book, you'll be well-equipped to build ML models in Power BI, plan projects for both BI and ML, understand R/Python visuals with Power BI, and introduce OpenAI to enhance your analytics solutions.What You Will Learn: Discover best practices for implementing AI and ML capabilities in Power BI along with integration of OpenAI into the solutionUnderstand how to integrate OpenAI and cognitive services into Power BIExplore how to build a SaaS auto ML model within Power BIGain an understanding of R/Python integration with Power BIEnhance data visualizations for ML feature discoveryDiscover how to improve existing solutions and workloads using AI and ML capabilities in Power BI with OpenAIAcquire tips and tricks for successfully using AI and ML capabilities in Power BI along with integration of OpenAI into the solutionWho this book is for: This book is for data science and BI professionals looking to expand their skill sets into Power BI machine learning and OpenAI. This book is also useful for data scientists, data analysts, and IT professionals who want to learn how to incorporate OpenAI into Power BI for advanced experience
Natural Language Understanding with Python
Build advanced NLU systems by utilizing NLP libraries such as NLTK, SpaCy, BERT, and OpenAI; ML libraries like Keras, scikit-learn, pandas, TensorFlow, and NumPy, along with visualization libraries such as Matplotlib and Seaborn. Purchase of the print Kindle book includes a free PDF eBookKey Features: Master NLU concepts from basic text processing to advanced deep learning techniquesExplore practical NLU applications like chatbots, sentiment analysis, and language translationGain a deeper understanding of large language models like ChatGPTBook Description: Natural language understanding (NLU) organizes and structures, language allowing computer systems to effectively process textual information for many different practical applications. Natural Language Understanding with Python will help you explore practical techniques that make use of NLU to build a wide variety of creative and useful applications.Complete with step-by-step explanations of essential concepts and practical examples, this book begins by teaching you about NLU and its applications. You'll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you'll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you'll also be introduced to practical issues such as acquiring data, evaluating systems, and deploying NLU applications, along with their solutions. This book is a comprehensive guide that will help you explore the full spectrum of essential NLU techniques and resources.By the end of this book, you will be familiar with the foundational concepts of NLU, deep learning, and large language models (LLMs). You will be well on your way to having the skills to independently apply NLU technology in your own academic and practical applications.What You Will Learn: Explore the uses and applications of different NLP techniquesUnderstand practical data acquisition and system evaluation workflowsBuild cutting-edge and practical NLP applications to solve problemsMaster NLP development from selecting an application to deploymentOptimize NLP application maintenance after deploymentBuild a strong foundation in neural networks and deep learning for NLUWho this book is for: This book is for python developers, computational linguists, linguists, data scientists, NLP developers, conversational AI developers, and students looking to learn about natural language understanding (NLU) and applying natural language processing (NLP) technology to real problems. Anyone interested in addressing natural language problems will find this book useful. Working knowledge in Python is a must.
Kafka Connect
Used by more than 80% of Fortune 100 companies, Apache Kafka has become the de facto event streaming platform. Kafka Connect is a key component of Kafka that lets you flow data between your existing systems and Kafka to process data in real time. With this practical guide, authors Mickael Maison and Kate Stanley show data engineers, site reliability engineers, and application developers how to build data pipelines between Kafka clusters and a variety of data sources and sinks. Kafka Connect allows you to quickly adopt Kafka by tapping into existing data and enabling many advanced use cases. No matter where you are in your event streaming journey, Kafka Connect is the ideal tool for building a modern data pipeline. Learn Kafka Connect's capabilities, main concepts, and terminology Design data and event streaming pipelines that use Kafka Connect Configure and operate Kafka Connect environments at scale Deploy secured and highly available Kafka Connect clusters Build sink and source connectors and single message transforms and converters
Engineering Psychology and Cognitive Ergonomics
This two-volume set LNCS 14017 - 14018 constitutes the thoroughly refereed proceedings of the 20th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2023, held as part of HCI International 2023 which took place in Copenhagen, Denmark, during July 23-28, 2023.A total of 1578 papers and 396 posters have been accepted for publication in the HCII 2023 proceedings from a total of 7472 submissions. The papers included in the HCII-EPCE volume set were organized in topical sections as follows: Part I: Stress, fatigue, and mental workload; human performance and error management; resilience and performance in demanding contexts. Part II: Human factors in aviation; human factors in operations management; human-centered design of autonomous systems.
Learn Ai-Assisted Python Programming
Writing computer programs in Python just got a lot easier! Use AI-assisted coding tools like GitHub Copilot and ChatGPT to turn your ideas into applications faster than ever. AI has changed the way we write computer programs. With tools like Copilot and ChatGPT, you can describe what you want in plain English, and watch your AI assistant generate the code right before your eyes. It's perfect for beginners, or anyone who's struggled with the steep learning curve of traditional programming. In Learn AI-Assisted Python Programming: With GitHub Copilot and ChatGPT you'll learn how to: Write fun and useful Python applications--no programming experience required! Use the Copilot AI coding assistant to create Python programs Write prompts that tell Copilot exactly what to do Read Python code and understand what it does Test your programs to make sure they work the way you want them to Fix code with prompt engineering or human tweaks Apply Python creatively to help out on the job Learn AI-Assisted Python Programming: With GitHub Copilot and ChatGPT is a hands-on beginner's guide that is written by two esteemed computer science university professors. It teaches you everything you need to start programming Python in an AI-first world. You'll hit the ground running, writing prompts that tell your AI-assistant exactly what you want your programs to do. Along the way, you'll pick up the essentials of Python programming and practice the higher-level thinking you'll need to create working apps for data analysis, automating tedious tasks, and even video games. Foreword by Beth Simon, Ph.D. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology The way people write computer programs has changed forever. Using GitHub Copilot, you describe in plain English what you want your program to do, and the AI generates it instantly. About the book This book shows you how to create and improve Python programs using AI--even if you've never written a line of computer code before. Spend less time on the slow, low-level programming details and instead learn how an AI assistant can bring your ideas to life immediately. As you go, you'll even learn enough of the Python language to understand and improve what your AI assistant creates. What's inside Prompts for working code Tweak code manually and with AI help AI-test your programs Let AI handle tedious details About the reader If you can move files around on your computer and install new programs, you can learn to write useful software! About the author Dr. Leo Porter is a Teaching Professor at UC San Diego. Dr. Daniel Zingaro is an Associate Teaching Professor at the University of Toronto. The technical editor on this book was Peter Morgan. Table of Contents 1 Introducing AI-assisted programming with Copilot 2 Getting started with Copilot 3 Designing functions 4 Reading Python code - Part 1 5 Reading Python Code - Part 2 6 Testing and prompt engineering 7 Problem decomposition 8 Debugging and better understanding your code 9 Automating tedious tasks 10 Making some games 11 Future directions
Advanced Strategies for AI-Driven Crypto Investing
Are you tired of conventional investment strategies that no longer yield significant returns? Have you been considering the increasingly popular avenue of cryptocurrency investing but are unsure of how to navigate the complexities and risks that come with it? Look no further than "Advanced Strategies for AI-Driven Crypto Investing."This book offers cutting-edge insights into the world of cryptocurrency investing, providing a comprehensive guide to advanced techniques that utilize artificial intelligence and machine learning to maximize returns while mitigating risk. The authors have combined their years of expertise in both finance and technology to create a truly unparalleled resource for investors seeking to stay ahead of the curve.Chapter One delves into deep learning strategies for crypto investing, offering readers a fundamental understanding of the underlying principles of AI and how they can be applied to cryptocurrency markets. Chapter Two explores the fascinating field of natural language processing, which allows investors to make more informed decisions by analyzing vast amounts of data from a wide range of sources.Chapter Three offers an in-depth examination of the evolution of cryptocurrency trading bots, demonstrating how they have transformed the landscape of crypto investing and how investors can leverage these powerful tools to gain an edge in the market. Chapter Four provides a comprehensive overview of advanced portfolio management techniques, including machine learning algorithms, risk management strategies, and alternative approaches to modern portfolio theory.Chapter Five focuses on risk management in highly volatile cryptocurrency markets, including scenario analysis and stress testing for assessing portfolio risk and hedging strategies using options and futures contracts. Chapter Six tackles the complex world of regulatory considerations for AI-driven crypto investing, outlining the current regulations surrounding cryptocurrency investing and exploring the potential impact of future regulations.The conclusion ties everything together, providing practical steps for implementing advanced AI strategies in cryptocurrency investing and offering a glimpse into the future of this exciting and rapidly evolving field."Advanced Strategies for AI-Driven Crypto Investing" is a must-read for anyone seeking to take their cryptocurrency investing to the next level. Whether you're a seasoned investor or just starting out, this book will provide invaluable insights and strategies that will help you navigate the complexities of the cryptocurrency market with confidence and success. Don't miss out on this game-changing resource - get your copy today!
R for Data Science
Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse璽 a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly. You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way. You'll understand how to: Visualize: Create plots for data exploration and communication of results Transform: Discover variable types and the tools to work with them Import: Get data into R and in a form convenient for analysis Program: Learn R tools for solving data problems with greater clarity and ease Communicate: Integrate prose, code, and results with Quarto
Financial Modeling Using Quantum Computing
Elevate your problem-solving prowess by using cutting-edge quantum machine learning algorithms in the financial domainPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn to solve financial analysis problems by harnessing quantum powerUnlock the benefits of quantum machine learning and its potential to solve problemsTrain QML to solve portfolio optimization and risk analytics problemsBook DescriptionQuantum computing has the potential to revolutionize the computing paradigm. By integrating quantum algorithms with artificial intelligence and machine learning, we can harness the power of qubits to deliver comprehensive and optimized solutions for intricate financial problems.This book offers step-by-step guidance on using various quantum algorithm frameworks within a Python environment, enabling you to tackle business challenges in finance. With the use of contrasting solutions from well-known Python libraries with quantum algorithms, you'll discover the advantages of the quantum approach. Focusing on clarity, the authors expertly present complex quantum algorithms in a straightforward, yet comprehensive way. Throughout the book, you'll become adept at working with simple programs illustrating quantum computing principles. Gradually, you'll progress to more sophisticated programs and algorithms that harness the full power of quantum computing.By the end of this book, you'll be able to design, implement and run your own quantum computing programs to turbocharge your financial modelling.What you will learnExamine quantum computing frameworks, models, and techniquesGet to grips with QC's impact on financial modelling and simulationsUtilize Qiskit and Pennylane for financial analysesEmploy renowned NISQ algorithms in model buildingDiscover best practices for QML algorithmSolve data mining issues with QML algorithmsWho this book is forThis book is for financial practitioners, quantitative analysts, or developers; looking to bring the power of quantum computing to their organizations. This is an essential resource written for finance professionals, who want to harness the power of quantum computers for solving real-world financial problems. A basic understanding of Python, calculus, linear algebra, and quantum computing is a prerequisite.Table of ContentsQuantum Computing ParadigmQuantum Machine Learning AlgorithmsQuantum Finance LandscapeDerivatives ValuationPortfolio ValuationsCredit Risk AnalyticsImplementation in Quantum CloudsHPCs and Simulators RelevanceNISQ Quantum Hardware EvolutionQuantum Roadmap for Banks and Fintechs
Machine Learning and AI in Clinical Practice
Machine Learning and AI in Clinical Practice: Revolutionizing Diagnosis and Treatment Strategies is a groundbreaking book that delves into the world of artificial intelligence (AI) and machine learning (ML) in healthcare. With advancements in technology, AI and ML have become integral parts of clinical practice, revolutionizing the way diagnoses are made and treatments are administered.This book provides a comprehensive overview of the latest AI and ML applications in healthcare, offering a glimpse into the future of medicine. From predicting treatment outcomes and identifying patient risk factors to drug discovery and personalized medicine, the potential applications of AI and ML in healthcare are limitless.The authors, a team of leading experts in the field, explore the benefits and challenges of using AI and ML in clinical practice, and provide valuable insights into the ethical and social considerations of this rapidly-evolving technology. They also discuss the potential impact on healthcare operations and the need for continued research and development to ensure the responsible use of AI and ML in medicine.Whether you are a healthcare professional, a researcher, or simply interested in the future of medicine, Machine Learning and AI in Clinical Practice is an essential guide to understanding the latest advancements in this exciting field. With detailed explanations of key concepts and real-world case studies, this book is both informative and accessible.Don't miss out on the opportunity to learn about the latest developments in AI and ML in healthcare. This book is a must-read for anyone interested in the future of medicine and the potential for technology to revolutionize clinical practice. Order your copy today and discover the endless possibilities of AI and ML in healthcare.
GIFTED GEEKS Emergence of Computer Tech Talent
In the past couple of decades, early adopters of technology have usually been children and teenagers, leaving many parents and teachers in awe of their knowledge and skills. The entire culture has been affected by these changes, as noted by Cross: "This generation of children who are now in their teens has become so technologically savvy that being passionate about technology is becoming more commonplace" (p. 26). According to recent PEW data, 87% of children 12-17 are on-line, and the percentage continues to increase (Fox & Madden, 2006). It seems that now more than ever it is important for schools to recognize young people demonstrating exceptional computer technology savvy, and provide pertinent talent development opportunities if these individuals are to realize their full potential.
AI Revolution in Law-Opportunities and Challenges
The world is changing at an unprecedented pace, and with the emergence of artificial intelligence (AI), the legal industry is no exception. AI is revolutionizing the way lawyers work and is creating new opportunities for increased efficiency, improved decision making, and enhanced access to justice.The AI Revolution in Law: Opportunities and Challenges is a comprehensive guide that explores the impact of AI on the legal industry. This book covers a wide range of topics, including legal research, contract review, predictive analytics, intellectual property law, e-discovery, legal writing, and the future of the legal industry.Through a series of in-depth discussions and case studies, the book provides readers with a comprehensive understanding of the potential benefits and challenges of AI in law. The authors have carefully curated the latest research and insights into the subject matter, providing readers with practical insights and strategies for incorporating AI into their practice.Whether you are a practicing attorney, law student, or a technology enthusiast, this book is a must-read. It provides a balanced and unbiased overview of the opportunities and challenges that AI presents to the legal industry.Readers will learn about the latest developments in AI technology, including natural language processing, machine learning, and deep learning. The authors also discuss the ethical implications of AI in law, highlighting the need for responsible development and use of this technology.The AI Revolution in Law: Opportunities and Challenges is an essential resource for anyone interested in the intersection of law and technology. It is a timely and thought-provoking book that offers valuable insights into the future of the legal industry.So, if you want to stay ahead of the curve and take advantage of the opportunities that AI presents to the legal industry, this is the book for you. Don't miss out on this opportunity to learn about the potential of AI in law and the challenges that lie ahead. Get your copy today!
Artificial Intelligence and legal-Balancing Efficiency, Fairness, and Accountability
Are you curious about the impact of artificial intelligence on the legal industry? Do you want to understand how AI can improve efficiency, increase fairness, and ensure accountability in the legal system? Then you won't want to miss "Artificial Intelligence and Legal: Balancing Efficiency, Fairness, and Accountability."In this groundbreaking book, leading experts explore the latest developments in AI and its applications in law. From contract review to predictive analytics to intellectual property law, they provide a comprehensive overview of how AI is transforming the legal industry. But this isn't just a technical manual. The authors also delve into the ethical implications of AI in law and the challenges and opportunities facing the legal profession in the age of automation.You'll discover how AI can streamline legal processes, reduce costs, and increase access to justice for all. But you'll also learn about the potential pitfalls, such as the risk of bias and the need to ensure transparency and accountability in AI decision-making. Through real-world examples and case studies, the authors provide a balanced and nuanced perspective on the use of AI in law.Whether you're a legal practitioner, a student of law, or simply interested in the intersection of technology and society, this book is a must-read. It will equip you with the knowledge and insights you need to navigate the fast-changing landscape of AI in law. You'll come away with a deeper understanding of the benefits and challenges of AI, as well as practical recommendations for how to ensure that AI is used ethically and responsibly in the legal industry.So don't wait any longer. Get your hands on "Artificial Intelligence and Legal: Balancing Efficiency, Fairness, and Accountability" today and join the conversation about the future of AI in law.
Entity Alignment
This open access book systematically investigates the topic of entity alignment, which aims to detect equivalent entities that are located in different knowledge graphs. Entity alignment represents an essential step in enhancing the quality of knowledge graphs, and hence is of significance to downstream applications, e.g., question answering and recommender systems. Recent years have witnessed a rapid increase in the number of entity alignment frameworks, while the relationships among them remain unclear. This book aims to fill that gap by elaborating the concept and categorization of entity alignment, reviewing recent advances in entity alignment approaches, and introducing novel scenarios and corresponding solutions.Specifically, the book includes comprehensive evaluations and detailed analyses of state-of-the-art entity alignment approaches and strives to provide a clear picture of the strengths and weaknesses of the currently available solutions, so as to inspire follow-upresearch. In addition, it identifies novel entity alignment scenarios and explores the issues of large-scale data, long-tail knowledge, scarce supervision signals, lack of labelled data, and multimodal knowledge, offering potential directions for future research. The book offers a valuable reference guide for junior researchers, covering the latest advances in entity alignment, and a valuable asset for senior researchers, sharing novel entity alignment scenarios and their solutions. Accordingly, it will appeal to a broad audience in the fields of knowledge bases, database management, artificial intelligence and big data.
Entity Alignment
This open access book systematically investigates the topic of entity alignment, which aims to detect equivalent entities that are located in different knowledge graphs. Entity alignment represents an essential step in enhancing the quality of knowledge graphs, and hence is of significance to downstream applications, e.g., question answering and recommender systems. Recent years have witnessed a rapid increase in the number of entity alignment frameworks, while the relationships among them remain unclear. This book aims to fill that gap by elaborating the concept and categorization of entity alignment, reviewing recent advances in entity alignment approaches, and introducing novel scenarios and corresponding solutions.Specifically, the book includes comprehensive evaluations and detailed analyses of state-of-the-art entity alignment approaches and strives to provide a clear picture of the strengths and weaknesses of the currently available solutions, so as to inspire follow-upresearch. In addition, it identifies novel entity alignment scenarios and explores the issues of large-scale data, long-tail knowledge, scarce supervision signals, lack of labelled data, and multimodal knowledge, offering potential directions for future research. The book offers a valuable reference guide for junior researchers, covering the latest advances in entity alignment, and a valuable asset for senior researchers, sharing novel entity alignment scenarios and their solutions. Accordingly, it will appeal to a broad audience in the fields of knowledge bases, database management, artificial intelligence and big data.
Mobile Networks and Management
This book constitutes the refereed post-conference proceedings of the 12th EAI International Conference on Mobile Networks and Management, MONAMI 2022, which took place virtually during October 29-31, 2022.The 31 full papers were carefully reviewed and selected from 78 submissions. The papers are divided into groups of content as follows: Innovative Artificial Intelligence Applications for Smart City; The New Era of Computer Network by using Machine Learning; Advanced Technologies in Edge and Fog Computing; Emerging Technologies in Mobile Networks and Management; and Recent Advances in Communications and Computing.
Neo4j Data Modeling
The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications. Read Neo4j Data Modeling if you are a data professional who needs to expand your modeling skills to include Neo4j or a technologist who knows Neo4j but needs to grow your schema design skills.The book's introduction and three chapters cover the Align, Refine, and Design approach. We include what the level does in the name by rebranding Conceptual, Logical, and Physical into Align, Refine, and Design. The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Chapter 1, Align, is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Chapter 2, Refine, is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Chapter 3, Design, is about the technical requirements. That is, designing to accommodate our model's unique software and hardware needs.Align, Refine, and Design-that's the approach followed in this book and reinforced through an animal shelter case study. If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.
MongoDB Data Modeling and Schema Design
The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications. Read MongoDB Data Modeling and Schema Design if you are a data professional who needs to expand your modeling skills to include MongoDB or a technologist who knows MongoDB but needs to grow your schema design skills.The book's introduction and three chapters cover the Align, Refine, and Design approach. We include what the level does in the name by rebranding Conceptual, Logical, and Physical into Align, Refine, and Design. The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Chapter 1, Align, is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Chapter 2, Refine, is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Chapter 3, Design, is about the technical requirements. That is, designing to accommodate our model's unique software and hardware needs.Align, Refine, and Design-that's the approach followed in this book and reinforced through an animal shelter case study. If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.
Internet of Things
Have you ever wondered how the technology that is shaping our world works?From mainstream technologies such as computing and the Internet, to emerging technologies such as artificial intelligence and quantum computing, it is no secret that the world is heavily influenced by technology. Yet, the technology that we depend upon is often not fully understood by those not specialized in the field. You are going to learn: What the internet of things really is (and what it is not)How the internet of things is going to affect our livesHow the iot & smart homes will change our householdsWhat iot means for corporations & their business modelsThe main benefits if iot (this will surprise you)Current shortcomings in iot to watch out forThis book is an essential resource for engineers, developers, and data scientists working in the field of industrial IoT. Whether you're a beginner or an experienced practitioner, this book will provide you with the knowledge and skills you need to build effective predictive maintenance systems for industrial IoT applications
Data Modeling with Snowflake
Discover how Snowflake's unique objects and features can be used to leverage universal modeling techniques through real-world examples and SQL recipesPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn core modeling techniques tied to practical examples using native Snowflake architectureAdopt a universal modeling language to communicate business value to functional teamsGo beyond physical modeling with SQL recipes to transform and shape your Snowflake dataBook DescriptionThe Snowflake Data Cloud is one of the fastest-growing platforms for data warehousing and application workloads. Snowflake's scalable, cloud-native architecture and expansive set of features and objects enables you to deliver data solutions quicker than ever before. Yet, we must ensure that these solutions are developed using recommended design patterns and accompanied by documentation that's easily accessible to everyone in the organization. This book will help you get familiar with simple and practical data modeling frameworks that accelerate agile design and evolve with the project from concept to code. These universal principles have helped guide database design for decades, and this book pairs them with unique Snowflake-native objects and examples like never before - giving you a two-for-one crash course in theory as well as direct application. By the end of this Snowflake book, you'll have learned how to leverage Snowflake's innovative features, such as time travel, zero-copy cloning, and change-data-capture, to create cost-effective, efficient designs through time-tested modeling principles that are easily digestible when coupled with real-world examples.What you will learnDiscover the time-saving features and applications of data modelingExplore Snowflake's cloud-native architecture and featuresUnderstand and apply modeling concepts, techniques, and language using Snowflake objectsMaster modeling concepts such as normalization and slowly changing dimensionsGet comfortable reading and transforming semi-structured dataWork directly with pre-built recipes and examplesApply modeling frameworks from Star to Data VaultWho this book is forThis book is for developers working with SQL who are looking to build a strong foundation in modeling best practices and gain an understanding of where they can be effectively applied to save time and effort. Whether you're an ace in SQL logic or starting out in database design, this book will equip you with the practical foundations of data modeling to guide you on your data journey with Snowflake. Developers who've recently discovered Snowflake will be able to uncover its core features and learn to incorporate them into universal modeling frameworks.Table of ContentsUnlocking the Power of ModelingAn Introduction to the Four Modeling TypesMastering Snowflake's ArchitectureMastering Snowflake ObjectsSpeaking Modeling through Snowflake ObjectsSeeing Snowflake's Architecture through Modeling NotationPutting Conceptual Modeling into PracticePutting Logical Modeling into PracticeDatabase NormalizationDatabase Naming and StructurePutting Physical Modeling into PracticePutting Transformational Modeling into PracticeModeling Slowly Changing DimensionsModeling Facts for Rapid AnalysisModeling Semi-Structured DataModeling HierarchiesScaling Data Models through Modern TechniquesAppendix
Server and Data Center Technologies
This is the fourth edition of a generalized hardware exercise and study manual for servers and data centers. It is designed to accompany a lecture based component that consists of twenty-eight modules covering material based on principles of a basic understanding of computer hardware and operating system interactions. This manual is designed to be used in a variety of teaching environments and has utilized generic server equipment for adaption to various academic programs.
Practical Guide to Azure Cognitive Services
Streamline your complex processes and optimize your organization's operational efficiency, cost-effectiveness, and customer experience by unlocking the potential of Microsoft Azure Cognitive Services and OpenAIPurchase of the print or Kindle book includes a free PDF eBookKey Features: Minimize costs and maximize operations by automating mundane activities using AI toolsIdeate solutions using real-world examples for manufacturing process improvement with AIMaster TCO and ROI analysis for implementing AI solutions, automating operations, and ideating innovative manufacturing solutions with real-world examplesBook Description: Azure Cognitive Services and OpenAI are a set of pre-built AI solution APIs that can be leveraged from existing applications, allowing customers to take advantage of Microsoft's award-winning Vision, Speech, Text, Decision, and GPT-4 AI (artificial intelligence) capabilities.With A Practical Guide to Azure Cognitive Services, you'll work with manufacturing industry-specific examples of implementations to head-start your production journey. You'll begin with an overview of categorization of Azure Cognitive Services and the benefits of embracing AI solutions for practical business applications. Next, you'll explore the benefits of using Azure Cognitive Services to optimize efficiency and improve predictive capabilities. Later, you'll learn to leverage Vision capabilities for quality control, Forms Recognizer to streamline supply chain nuances, language understanding for improving customer service, and Cognitive Search for a next-generation knowledge mining solutions, and more.By the end of this book, you'll be able to implement various Cognitive Services solutions that will help you enhance efficiency, reduce costs, and improve customer experience at your organization. You'll also be well-equipped to automate mundane tasks by reaping the full potential of OpenAI.What You Will Learn: Master cost-effective deployment of Azure Cognitive ServicesDevelop proven solutions from an architecture and development standpointUnderstand how Cognitive Services are deployed and customizedEvaluate various uses of Cognitive Services with different mediumsDisseminate Azure costs for Cognitive Services workloads smoothlyDeploy next-generation Knowledge Mining solutions with Cognitive SearchExplore the current and future journey of OpenAIUnderstand the value proposition of different AI projectsWho this book is for: This book is for data scientists, technology leaders, and software engineers looking to implement Azure Cognitive Services with the help of sample use cases derived from success stories. Experience with Python as well as an overall understanding of the Azure Portal with related services such as Azure Data Lake Storage and Azure Functions will help you make the most of this book.
The Joy of Mindful Tech
Are you tired of feeling overwhelmed by the constant barrage of technology in your life? Do you want to reclaim your time and attention while still benefiting from the latest advancements? Look no further than "The Joy of Mindful Tech: Minimalism in the Age of Blockchain and AI."This groundbreaking book offers a fresh perspective on technology, introducing the concept of minimalist tech - the idea that we can use technology in a mindful, intentional way to enhance our lives rather than detract from them. Through a comprehensive exploration of the history of technology, the basics of blockchain and AI, and the ethical considerations of technology, readers will gain a deeper understanding of how to integrate mindful tech practices into their daily lives.With practical tips and actionable advice, readers will learn how to approach technology in a more minimalist way, including reducing digital clutter, practicing mindful consumption, and embracing a more intentional approach to technology use. Through case studies of individuals and companies who have successfully implemented minimalist tech practices, readers will see firsthand the benefits of a more mindful approach to technology.But this book isn't just about personal growth - it's about creating a better world through the intersection of technology and minimalism. The author explores the potential impact of minimalist tech on society and the environment, as well as the ethical considerations of technology use. Readers will gain a deeper understanding of the responsibility that comes with being a tech user in today's world, and how we can all work towards a more sustainable and fulfilling future."The Joy of Mindful Tech" is the ultimate guide for anyone looking to take control of their relationship with technology and create a more intentional and fulfilling life. Don't miss out on this transformative book - get your copy today and start your journey towards mindful tech practices.
This Robot Brain Gets Life (Making AI Pseudo-Conscious)
For those in a hurry, this:  To align an AI's goals with ours, we must build-in alignment from the start, To keep an AI honest, we must build-in honesty from the start, To get an AI to understand anything, we must invest it with something of what it's like to be conscious. In this book, a theory of consciousness is cast into an AI architecture that allows interventions in concept formation by design. For the rest of you, who enjoy reading and mulling things over, this: Can a computing device appreciate the smell of coffee on a Sunday morning, or contemplate the Earth as seen from the Moon, or worry about inflation and the price of fuel? Not without being conscious and understanding the world. And one can't be done without the other, surely? In this book, Carter Blakelaw uses a theory of what makes us conscious to present a machine that will genuinely think for itself. Not only that, but once he has his machine, he looks at how to ensure its interests align with our own, and how to keep it honest and true (alignment and hallucinations being two of the biggest issues in AI). Discover what he discovers about the machine, about our world, and about us.
AWS Observability Handbook
Accelerate cloud adoption using AWS CloudWatch, X-ray, Distro for OpenTelemetry, Amazon DevOps Guru, and more to monitor and build resilient systemsPurchase of the print or Kindle book includes a free PDF eBookKey Features: Gain a thorough understanding of observability principles along with different AWS service offerings and best practicesEnsure customer satisfaction by monitoring user experience and fixing bottlenecks quicklyLearn from experts to get the best possible insights into AWS' observability solutionsBook Description: As modern application architecture grows increasingly complex, identifying potential points of failure and measuring end user satisfaction, in addition to monitoring application availability, is key. This book helps you explore AWS observability tools that provide end-to-end visibility, enabling quick identification of performance bottlenecks in distributed applications.You'll gain a holistic view of monitoring and observability on AWS, starting from observability basics using Amazon CloudWatch and AWS X-Ray to advanced ML-powered tools such as AWS DevOps Guru. As you progress, you'll learn about AWS-managed open source services such as AWS Distro for OpenTelemetry (ADOT) and AWS managed Prometheus, Grafana, and the ELK Stack. You'll implement observability in EC2 instances, containers, Kubernetes, and serverless apps and grasp UX monitoring. With a fair mix of concepts and examples, this book helps you gain hands-on experience in implementing end-to-end AWS observability in your applications and navigating and troubleshooting performance issues with the help of use cases. You'll also learn best practices and guidelines, such as how observability relates to the Well-Architected Framework.By the end of this AWS book, you'll be able to implement observability and monitoring in your apps using AWS' native and managed open source tools in real-world scenarios.What You Will Learn: Capture metrics from an EC2 instance and visualize them on a dashboardConduct distributed tracing using AWS X-RayDerive operational metrics and set up alerting using CloudWatchAchieve observability of containerized applications in ECS and EKSExplore the practical implementation of observability for AWS LambdaObserve your applications using Amazon managed Prometheus, Grafana, and OpenSearch servicesGain insights into operational data using ML services on AWSUnderstand the role of observability in the cloud adoption frameworkWho this book is for: This book is for SREs, DevOps and cloud engineers, and developers who are looking to achieve their observability targets using AWS native services and open source managed services on AWS. It will assist solution architects in achieving operational excellence by implementing cloud observability solutions for their workloads. Basic understanding of AWS cloud fundamentals and different AWS cloud services used to run applications such as EC2, container solutions such as ECS, and EKS will be helpful when using this book.
SQL Server 2022 Administration Inside Out
Conquer SQL Server 2022 and Azure SQL administration from the inside out! Dive into SQL Server 2022 administration and grow your Microsoft SQL Server data platform skillset. This well-organized reference packs in timesaving solutions, tips, and workarounds, all you need to plan, implement, deploy, provision, manage, and secure SQL Server 2022 in any environment: on-premises, cloud, or hybrid, including detailed, dedicated chapters on Azure SQL Database and Azure SQL Managed Instance. Nine experts thoroughly tour DBA capabilities available in the SQL Server 2022 Database Engine, SQL Server Data Tools, SQL Server Management Studio, PowerShell, and much more. You'll find extensive new coverage of Azure SQL Database and Azure SQL Managed Instance, both as a cloud platform of SQL Server and in their new integrations with SQL Server 2022, information available in no other book. Discover how experts tackle today's essential tasks and challenge yourself to new levels of mastery. Identify low-hanging fruit and practical, easy wins for improving SQL Server administration Get started with modern SQL Server tools, including SQL Server Management Studio, and Azure Data Studio Upgrade your SQL Server administration skillset to new features of SQL Server 2022, Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Linux Design and implement modern on-premises database infrastructure, including Kubernetes Leverage data virtualization of third-party or non-relational data sources Monitor SQL instances for corruption, index activity, fragmentation, and extended events Automate maintenance plans, database mail, jobs, alerts, proxies, and event forwarding Protect data through encryption, privacy, and auditing Provision, manage, scale and secure, and bidirectionally synchronize Microsoft's powerful Azure SQL Managed Instance Understand and enable new Intelligent Query Processing features to increase query concurrency Prepare a best-practice runbook for disaster recovery Use SQL Server 2022 features to span infrastructure across hybrid environments
The Future of Intelligence
Discover the revolutionary technology that's changing the way we live, work, and think. From self-driving cars to virtual assistants, artificial intelligence (AI) is transforming the world as we know it. But what exactly is AI, and how does it work? In this comprehensive guide, you'll learn everything you need to know about AI, from its origins and history to the latest developments and breakthroughs. Written by three experts in the field, this book provides a clear and accessible introduction to the concepts and techniques of AI, including machine learning, neural networks, and natural language processing. But this book isn't just about theory - it's also about practice. You'll discover how AI is being used in a wide range of industries, from healthcare and finance to entertainment and transportation. You'll learn about the opportunities and challenges of implementing AI in your own organization, and the ethical considerations that come with creating intelligent machines. Whether you're a student, a professional, or just curious about the world of AI, this book is an essential resource for anyone who wants to understand one of the most exciting and transformative technologies of our time. So why wait? Start exploring the possibilities of AI today!
Cognitive Computation and Systems
This volume constitutes selected papers presented during the First International Conference on Cognitive Computation and Systems, ICCCS 2022, held in Beijing, China, in October 2022.The 31 papers were thoroughly reviewed and selected from the 75 submissions. The papers are organized in topical sections on ​computer vision; decision making and cognitive computation; robot and autonomous vehicle.
Principles of Data Fabric
Apply data fabric solutions to automate data integration, data sharing, and data protection across disparate data sources without moving your dataPurchase of the print or Kindle book includes a free PDF eBookKey Features: Learn to design data fabric architecture effectively with your choice of toolBuild and use a data fabric solution using DataOps and data mesh frameworksFind out how to build data integration, data governance, and self-service analytics architectureBook Description: Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered.The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You'll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you'll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles.By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution.What You Will Learn: Understand the core components of Data Fabric solutionsCombine Data Fabric with Data Mesh and DataOps frameworksImplement distributed data management and regulatory compliance using Data FabricManage and enforce Data Governance with active metadata using Data FabricExplore industry best practices for effectively implementing a Data Fabric solutionWho this book is for: If you are a data engineer, data architect, or business analyst who wants to learn all about implementing data fabric architecture, then this is the book for you. This book will also benefit senior data professionals such as chief data officers looking to integrate data fabric architecture into the broader ecosystem.
Next Generation Arithmetic
This book constitutes the refereed proceedings of the 4th International Conference on Next Generation Arithmetic, CoNGA 2023, held in Singapore, during March 1-2, 2023.The 11 full papers in this book were carefully reviewed and selected from 16 submissions. They were organized in topical sections as follows: Lossless FFTs Using Posit Arithmetic, PLAUs: Posit Logarithmic Approximate Units to Implement Low-Cost Operations with Real Numbers.
Applications of Computational Intelligence
​This book constitutes the refereed proceedings of the 5th IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2022, held in Cali, Colombia during July 27-29, 2022. The 7 extended papers included in this book were carefully reviewed and selected from 38 submissions. They were organized in topical sections as follows: ​Design of a segmentation and classification system for seed detection based on pixel intensity thresholds and convolutional neural networks.
AI Chatbots And Social Apps
Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that would normally require human intelligence, such as problem-solving, decision-making, and learning. The field of AI is rapidly evolving, and new breakthroughs are being made at an unprecedented pace. Thanks to advances in machine learning and deep learning algorithms, AI systems can now recognize patterns in large amounts of data, enabling them to make predictions and identify insights that would be difficult or impossible for humans to discern. This has led to the development of powerful new AI applications in fields such as healthcare, finance, and transportation. With the growth of big data and the increasing availability of computing power, AI is expected to continue advancing at an exponential rate, with new breakthroughs and applications emerging at an ever-accelerating pace. As such, AI is poised to become one of the most transformative technologies of our time, with the potential to revolutionize nearly every aspect of our lives. You must read this!
State Space Systems With Time-Delays Analysis, Identification, and Applications
State Space Systems with Time-Delays Analysis, Identification and Applications covers the modeling, identification and control of industrial applications, including system identification, parameter estimation, dynamic simulation, nonlinear control, and other emerging techniques. The book introduces basic time-delay systems, architectures and control methods. Emphasis is placed on the mathematical analysis of these systems, identifying them, and applying them to practical engineering problems such as three independent water tank systems and distillation systems. This book contains a wide range of time-delay system identification methods that can help readers master the system controllers' design methods.
Active Inference
This volume constitutes the papers of the 3rd International Workshop on Active Inference, IWAI 2022, held in Grenoble, France, in conjunction with ECML/PKDD, on September 19, 2022.The 25 revised full papers presented in this book were carefully reviewed and selected from 31 submissions.
Artificial Life and Evolutionary Computation
This book constitutes the refereed proceedings of the 16th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2022, held in Gaeta, Italy, during September 14-16, 2022. The 21 full papers and 3 short papers included in this book were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: answer set programming; networks and complex systems, metaheuristics, robotics, and machine learningChapters 7, 8, and 9 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Development Of Artificial Intelligence Based E Learning System
Today e-learning system plays an essential role in the education system. Technologyintegration in teaching helps to teach content-based curriculum effectively andefficiently to build confidence among students. Personalized learning systems focus onlearning behavior, interest, and design curriculum according to learners' ability andbasic knowledge. It is a flexible teaching methodology to meet the individual needs ofstudents. The personalized learning approach optimizes the needs of each learner. Foran effective education system, it is necessary to understand learners and develop a planthat copes up with the individual learning needs and the interest of students'. Anintelligent Tutor system is an expert system to monitor the learners' performance toprovide personalized coaching. E-learning applications include computer-basedlearning, web-based learning, digital collaboration and virtual classrooms. ArtificialIntelligence can be used for automating learning activities like designing teaching tools, curriculum, training, evaluating students' performance, and using modern teachingmethodology. Artificial intelligence is the most modern e-learning trend in highereducation and the corporate world. AI helps to provide individual decisions using dataanalytics that leads to better education for personalized instruction to streamline theeducation process.
Data Journey
Every one of us generates an enormous amount of data every day through mobile devices or through social media, like Facebook, Instagram, or Twitter, or through any digital transactions like online shopping, banking transactions, etc. Organizations use those data for better understanding of business and customer behaviours. Data Journey, addresses all the key processes that involve converting raw data into insight. It deals in detail with the major and latest techniques, in each data journey stage, which include data collection, data storage, data transformation, data analysis, and data visualization. The book contains an overview of different AI/ML, Data mining, and Big Data techniques. It is also helpful to understand data security and governance. Multiple use cases are included in the topic, that will help to understand the importance of particular topics, and how industries are solving industrial challenges using the data. This book can serve as an excellent handbook, for researchers and anyone, who wants to learn more about the data and everything about the data.
Aixia 2022 - Advances in Artificial Intelligence
​This book constitutes the refereed proceedings of the XXIst International Conference of the Italian Association for Artificial Intelligence on AIxIA 2022 - Advances in Artificial Intelligence, which was held in Udine, Italy, during November 28-December 2, 2022.The 33 full papers and 1 invited paper presented in this volume were carefully reviewed and selected from 54 submissions. They were organized in topical sections as follows: Hybrid Approaches; Graphs and Networks; Multiagent Systems; Automated Planning and Scheduling; AI Applications; Miscellany; Natural Language Processing; and Keynote talk.
Explainable Deep Learning AI
Explainable Deep Learning AI: Methods and Challenges presents the latest works of leading researchers in the XAI area, offering an overview of the XAI area, along with several novel technical methods and applications that address explainability challenges for deep learning AI systems. The book overviews XAI and then covers a number of specific technical works and approaches for deep learning, ranging from general XAI methods to specific XAI applications, and finally, with user-oriented evaluation approaches. It also explores the main categories of explainable AI - deep learning, which become the necessary condition in various applications of artificial intelligence. The groups of methods such as back-propagation and perturbation-based methods are explained, and the application to various kinds of data classification are presented.
Research Productivity on Artificial Intelligence a Scientometric Study
A thorough and analytical work entitled "Research Productivity on Artificial Intelligence: A Scientometric Study" by R. Veerakumar examines the productivity and influence of research in the area of artificial intelligence (AI) through scientometric analysis. The book offers a thorough examination of the publication patterns, citation patterns, and research trends of AI research articles during the previous few decades. By showcasing the most important authors, organisations, and nations that have contributed to this subject, it provides insightful information about the expansion and development of the AI research community.For academics and researchers interested in AI and scientometric analysis, the book provides a great reference. Advanced research methods have been used by the author to present a thorough and instructive analysis of the subject. The book discusses a variety of subjects, such as the development of AI research, the effects of open access publishing, and the formation of new AI study fields.For everyone interested in the present state and prospects of AI research, "Research Productivity on Artificial Intelligence: A Scientometric Analysis" is a must-read. It is a useful tool for academics, researchers, politicians, and business executives involved in the field of AI. The book's in-depth analysis and insights will help readers better comprehend the most recent trends and advancements in AI research as well as how they will affect society.
Bio-Inspired Computing: Theories and Applications
This book constitutes the refereed proceedings of the 17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022, held in Wuhan, China, during December 16-18, 2022.The 56 full papers included in this book were carefully reviewed and selected from 148 submissions. They were organized in topical sections as follows: evolutionary computation and swarm intelligence; machine learning and deep learning; intelligent control and simulation and molecular computing and nanotechnology.
Analysis, Estimations, and Applications of Embedded Systems
This book constitutes the refereed proceedings of the 6th IFIP TC 10 International Embedded Systems Symposium, IESS 2019, which took place in Friedrichshafen, Germany, in September 2019. The 16 full papers and 4 short papers presented in this book were carefully reviewed and selected from 32 submissions. The papers were organized in topical sections on embedded real-time systems; estimations; architecture and applications; algorithms and System C; and analysis.
The Enterprise Data Catalog
Combing the web is simple, but how do you search for data at work? It's difficult and time-consuming, and can sometimes seem impossible. This book introduces a practical solution: the data catalog. Data analysts, data scientists, and data engineers will learn how to create true data discovery in their organizations, making the catalog a key enabler for data-driven innovation and data governance. Author Ole Olesen-Bagneux explains the benefits of implementing a data catalog. You'll learn how to organize data for your catalog, search for what you need, and manage data within the catalog. Written from a data management perspective and from a library and information science perspective, this book helps you: Learn what a data catalog is and how it can help your organization Organize data and its sources into domains and describe them with metadata Search data using very simple-to-complex search techniques and learn to browse in domains, data lineage, and graphs Manage the data in your company via a data catalog Implement a data catalog in a way that exactly matches the strategic priorities of your organization Understand what the future has in store for data catalogs
Cloud Computing Playbook
IF YOU WANT TO PASS THE MICROSOFT AZURE AZ-900 EXAM, OR WANT TO BECOME AN AWS CERTIFIED CLOUD PRACTITIONER, AND/OR WANT TO DISCOVER HOW TO AUTOMATE YOUR INFRASTRUCTURE ON ANY CLOUD WITH TERRAFORM, THIS BOOK IS FOR YOU!10 BOOKS IN 1 DEAL!- BOOK 1 - CLOUD COMPUTING FUNDAMENTALS: INTRODUCTION TO MICROSOFT AZURE AZ-900 EXAM- BOOK 2 - MICROSOFT AZURE SECURITY AND PRIVACY CONCEPTS: CLOUD DEPLOYMENT TOOLS AND TECHNIQUES, SECURITY & COMPLIANCE- BOOK 3 - MICROSOFT AZURE PRICING & SUPPORT OPTIONS: AZURE SUBSCRIPTIONS, MANAGEMENT GROUPS & COST MANAGEMENT- BOOK 4 - MICROSOFT AZURE AZ-900 EXAM PREPARATION GUIDE: HOW TO PREPARE, REGISTER AND PASS YOUR EXAM- BOOK 5 - AWS CLOUD PRACTITIONER: CLOUD COMPUTING ESSENTIALS- BOOK 6 - AWS CLOUD COMPUTING: INTRODUCTION TO CORE SERVICES- BOOK 7 - AWS CLOUD SECURITY: BEST PRACTICES FOR SMALL AND MEDIUM BUSINESSES- BOOK 8 - TERRAFORM FUNDAMENTALS: INFRASTRUCTURE DEPLOYMENT ACROSS MULTIPLE SERVICES- BOOK 9 - AUTOMATION WITH TERRAFORM: ADVANCED CONCEPTS AND FUNCTIONALITY- BOOK 10 - TERRAFORM CLOUD DEPLOYMENT: AUTOMATION, ORCHESTRATION, AND COLLABORATION GET THIS BOOK NOW AND BECOME A CLOUD PRO TODAY!
