- Table View
- List View
Expert Python Programming,: Become a master in Python by learning coding best practices and advanced programming concepts in Python 3.7, 3rd Edition
by Michał Jaworski Tarek ZiadéRefine your Python programming skills and build professional grade applications with this comprehensive guideKey FeaturesCreate manageable code that can run in various environments with different sets of dependenciesImplement effective Python data structures and algorithms to write optimized codeDiscover the exciting new features of Python 3.7Book DescriptionPython is a dynamic programming language that's used in a wide range of domains thanks to its simple yet powerful nature. Although writing Python code is easy, making it readable, reusable, and easy to maintain is challenging. Complete with best practices, useful tools, and standards implemented by professional Python developers, the third edition of Expert Python Programming will help you overcome this challenge.The book will start by taking you through the new features in Python 3.7. You'll then learn the advanced components of Python syntax, in addition to understanding how to apply concepts of various programming paradigms, including object-oriented programming, functional programming, and event-driven programming. This book will also guide you through learning the best naming practices, writing your own distributable Python packages, and getting up to speed with automated ways of deploying your software on remote servers. You’ll discover how to create useful Python extensions with C, C++, Cython, and CFFI. Furthermore, studying about code management tools, writing clear documentation, and exploring test-driven development will help you write clean code.By the end of the book, you will have become an expert in writing efficient and maintainable Python code.What you will learnExplore modern ways of setting up repeatable and consistent development environmentsPackage Python code effectively for community and production useLearn modern syntax elements of Python programming such as f-strings, enums, and lambda functionsDemystify metaprogramming in Python with metaclassesWrite concurrent code in PythonExtend Python with code written in different languagesIntegrate Python with code written in different languagesWho this book is forThis book will appeal to you if you’re a programmer looking to take your Python knowledge to the next level by writing efficient code and learning the latest features of version 3.7 and above.
Expert Python Programming: Master Python by learning the best coding practices and advanced programming concepts, 4th Edition
by Tarek Ziade Michal JaworskiAttain a deep understanding of building, maintaining, packaging, and shipping robust Python applicationsKey FeaturesDiscover the new features of Python, such as dictionary merge, the zoneinfo module, and structural pattern matchingCreate manageable code to run in various environments with different sets of dependenciesImplement effective Python data structures and algorithms to write, test, and optimize codeBook DescriptionPython is used in a wide range of domains owing to its simple yet powerful nature. Although writing Python code is easy, making it readable, reusable, and easy to maintain can be challenging. Complete with best practices, useful tools, and standards implemented by professional Python developers, this fourth edition will help you in not only overcoming such challenges but also learning Python's latest features and advanced concepts. The book begins with a warm-up, where you will catch-up with the latest Python improvements, syntax elements, and interesting tools to boost your development efficiency. Further, the initial few chapters should allow experienced programmers coming from different languages to safely land in the Python ecosystem. As you progress, you will explore common software design patterns and various programming methodologies, such as event-driven programming, concurrency, and metaprogramming. You will also go through complex code examples and try to solve meaningful problems by bridging Python with C and C++, writing extensions that benefit from the strengths of multiple languages. Finally, you will understand the complete lifetime of any application after it goes live. By the end of the book, you should be proficient in writing efficient and maintainable Python code.What you will learnExplore modern ways of setting up repeatable and consistent Python development environmentsEffectively package Python code for community and production useLearn about modern syntax elements of Python programming, such as f-strings, dataclasses, enums, and lambda functionsDemystify metaprogramming in Python with metaclassesWrite concurrent code in PythonMonitor and optimize the performance of Python applicationExtend and integrate Python with code written in different languagesWho this book is forThe Python programming book is intended for expert programmers who want to learn Python's advanced-level concepts and latest features.Anyone who has basic Python skills should be able to follow the content of the book, although it might require some additional effort from less experienced programmers. It should also be a good introduction to Python 3.9 for those who are still a bit behind and continue to use other older versions.
Expert SQL Server In-Memory OLTP
by Dmitri KorotkevitchExpert SQL Server In-Memory OLTP is a deep dive into one of the most significant features of SQL Server 2014 - support for In-Memory Online Transaction Processing. The book describes the architecture and internals of the In-Memory OLTP Engine and explains how to develop, deploy, and maintain systems using it. With it you can dramatically increase transactional throughput to handle thousands of transactions per second supporting millions of customers. Dmitri Korotkevitch is the five-star author of Pro SQL Server Internals, and now brings his same combination of clear thinking and deep expertise to the question of how to recognize the opportunities and benefit from Microsoft's In-Memory OLTP feature set in SQL Server 2014. Learn the architecture and the internals in order to recognize when in-memory OLTP can make a difference. Learn useful scenarios for thoughtfully incorporating In-Memory support into existing applications. Recognize opportunities for In-Memory OLTP in new development. Don't be without Dmitri Korotkevitch and the deep expertise he imparts in Expert SQL Server In-Memory OLTP as you move forward in using SQL Server's new and important In-Memory OLTP feature set. Covers In-Memory OLTP internals and architecture, including data storage, indexing, multi-version concurrency control, transaction logging, and recovery Illustrates In-Memory OLTP programmability and the process of native compilation Guides in using In-Memory OLTP in new development and existing systems. What you'll learn Grasp the internal mechanisms underlying in-memory tables and their implementation Plan successful implementations, including the required memory size and I/O configuration Properly index in-memory tables, including with hash indexes and range indexes Accelerate T-SQL processing through the creation of natively-compiled stored procedures Control disk I/O by managing logging, checkpoint, and recovery of in-memory data Monitor and report on the benefits and performance of your in-memory solutions Who this book is for Expert SQL Server In-Memory OLTP is for application developers and database administrators who create and manage online transaction processing (OLTP) systems. In particular, the book is aimed at those wanting to take advantage of SQL Server's new offering of in-memory OLTP to dramatically improve performance and throughput of their systems. Table of Contents Introduction 1. Why In-Memory OLTP? 2. In-Memory OLTP Objects 3. Memory-Optimized Tables 4. Hash Indexes 5. Nonclustered Indexes 6. In-Memory OLTP Prgrammability 7. In-Memory OLTP Concurrency Model 8. Data Storage, Logging, and Recovery 9. Garbage Collection 10. Deployment and Management 11. Utilizing In-Memory OLTP 12. Appendix A: Memory Pointer Management 13. Appendix B: Page Splitting and Merging in Nonclustered Indexes 14. Appendix C: Analyzing Checkpoint File Pair State 15. Appendix D: In-Memory OLTP Migration Tools
Expert SQL Server In-Memory OLTP
by Dmitri KorotkevitchExpert SQL Server In-Memory OLTP is a deep dive into one of the most significant features of SQL Server 2014 - support for In-Memory Online Transaction Processing. The book describes the architecture and internals of the In-Memory OLTP Engine and explains how to develop, deploy, and maintain systems using it. With it you can dramatically increase transactional throughput to handle thousands of transactions per second supporting millions of customers. Dmitri Korotkevitch is the five-star author of Pro SQL Server Internals, and now brings his same combination of clear thinking and deep expertise to the question of how to recognize the opportunities and benefit from Microsoft's In-Memory OLTP feature set in SQL Server 2014. Learn the architecture and the internals in order to recognize when In-Memory OLTP can make a difference. Learn useful scenarios for thoughtfully incorporating in-memory support into existing applications. Recognize opportunities for In-Memory OLTP in new development. Don't be without Dmitri Korotkevitch and the deep expertise he imparts in Expert SQL Server In-Memory OLTP as you move forward in using SQL Server's new and important In-Memory OLTP feature set. Covers In-Memory OLTP internals and architecture, including data storage, indexing, multi-version concurrency control, transaction logging, and recovery Illustrates In-Memory OLTP programmability and the process of native compilation Guides in using In-Memory OLTP in new development and existing systems.
Expert SQL Server Transactions and Locking: Concurrency Internals for SQL Server Practitioners
by Dmitri KorotkevitchMaster SQL Server’s Concurrency Model so you can implement high-throughput systems that deliver transactional consistency to your application customers. This book explains how to troubleshoot and address blocking problems and deadlocks, and write code and design database schemas to minimize concurrency issues in the systems you develop.SQL Server’s Concurrency Model is one of the least understood parts of the SQL Server Database Engine. Almost every SQL Server system experiences hard-to-explain concurrency and blocking issues, and it can be extremely confusing to solve those issues without a base of knowledge in the internals of the Engine. While confusing from the outside, the SQL Server Concurrency Model is based on several well-defined principles that are covered in this book.Understanding the internals surrounding SQL Server’s Concurrency Model helps you build high-throughput systems in multi-user environments. This book guides you through the Concurrency Model and elaborates how SQL Server supports transactional consistency in the databases. The book covers all versions of SQL Server, including Microsoft Azure SQL Database, and it includes coverage of new technologies such as In-Memory OLTP and Columnstore Indexes.What You'll LearnKnow how transaction isolation levels affect locking behavior and concurrencyTroubleshoot and address blocking issues and deadlocksProvide required data consistency while minimizing concurrency issuesDesign efficient transaction strategies that lead to scalable codeReduce concurrency problems through good schema designUnderstand concurrency models for In-Memory OLTP and Columnstore IndexesReduce blocking during index maintenance, batch data load, and similar tasksWho This Book Is ForSQL Server developers, database administrators, and application architects who are developing highly-concurrent applications. The book is for anyone interested in the technical aspects of creating and troubleshooting high-throughput systems that respond swiftly to user requests.
Expert Scripting and Automation for SQL Server DBAs: Amplifying Productivity Through Automation
by Peter A. CarterThe market is trending toward a much smaller ratio of DBAs to SQL Server instances, but this book will help you meet this new reality by harnessing automation to continue building and maintaining reliable database platform services for your SQL Server enterprise. The book will help you automate your workload and manage more databases and instances with greater ease and efficiency by combining metadata-driven automation with the power of PowerShell. You'll soon be able to automate your new instance-builds and centralize your maintenance. This book walks you through automating the SQL Server build processes and maintenance of multiple instances from a single location, as well as how to use database metadata to drive your automation. With a heavier focus on PowerShell, this 2nd edition highlights modern techniques, such as configuration management. Also new in this edition, you will learn how to use PowerShell modules such as SqlServer and DBATools, which is a popular community module that you can rely on to keep your database estate running smoothly. You will understand the benefits of centralizing maintenance to better keep your enterprise responding with reliable performance to the loads placed upon it by your business. The book helps you become faster and better at what you do for a living, and thus will boost your value within the job market. What You Will Learn Automate SQL Server installation and configuration Apply techniques such as Desired State Configuration to prevent drift on your servers and instances Increase your value to your organization by automating low-value tasks and focusing your time on the higher-value ones Take advantage of database metadata to drive automation, allowing you to build intelligent automated routines Promote and demonstrate how to modernize database maintenance across your enterprise Apply tools such as PowerShell with modern techniques to increase your value in the job market Who This Book Is For SQL Server DBAs who want to increase their productivity by embracing automation
Expert Secrets: The Underground Playbook for Converting Your Online Visitors into Lifelong Customers
by Russell BrunsonMaster the art of what to say in your funnels to convert your online visitors into lifelong customers in this updated edition from the $100M entrepreneur and co-founder of the software company ClickFunnels.Your business is a calling. You've been called to serve a group of people with the products, services, and offers that you've created. The impact that the right message can have on someone at the right time in their life is immeasurable. Your message could help to save marriages, repair families, change someone's health, grow a company, or more. . . . But only if you know how to get it into the hands of the people whose lives you have been called to change.By positioning yourself as an expert and telling your story in a way that gets people to move, you will be able to guide people through your value ladder, offer solutions to their problems, and give them the results they are looking for. This is how you change the lives of your customers, and this is how you grow your company.In this updated edition of Expert Secrets, Russell Brunson, CEO and co-founder of the multimillion-dollar software company ClickFunnels, gives you the step-by-step strategies you need to turn your expertise into a carefully crafted sales message that will attract your dream customers.Don't hide inside your business. Implement these story selling techniques now so you can find your voice and gain the confidence to become a leader, build a movement of people whose lives you can change, and make this calling a career.
Expert Sniper Strategies for Fortniters: An Unofficial Guide to Battle Royale (Master Combat)
by Jason RichHit your target every time with this Fortnite expert sniper guide. This all‑new, unofficial, illustrated guide series will turn you into a master Fortnite: Battle Royale gamer by uncovering all the best strategies and secrets of this wildly popular game. Whether you play Fortnite Battle Royale on a PC, Mac, Xbox One, PlayStation 4, or your mobile device, you’ll find everything you need to stay at the top of your game. Each book is packed with useful insider tips on topics like, staying alive longer, exploring, collecting a powerful arsenal, building, and snagging more victories during each match. When it comes to achieving #1 Victory Royale, the Fortnite Battle Royale: Master Combat Series provides the ultimate competitive edge. Thanks to this comprehensive how‑to Fortnite shooting guide, you’ll gain the crucial battle skills you need to eliminate your enemies like a pro. Sniper rifles and projectile weapons are only as good as the player using them. This comprehensive resource will sharpen your skills and show you how and when to use the incredible range of guns, weapons, tools, and ammunition available during each match. There’s nothing more important in Fortnite than staying alive longer and battling your way to #1 Victory Royale. This straightforward guide has everything you need to prepare for long‑range, mid‑range, and close‑range combat situations so that you can emerge a winner.
Expert Systems in Chemistry Research
by Markus C. HemmerExpert systems allow scientists to access, manage, and apply data and specialized knowledge from various disciplines to their own research. Expert Systems in Chemistry Research explains the general scientific basis and computational principles behind expert systems and demonstrates how they can improve the efficiency of scientific workflows
Expert T-SQL Window Functions in SQL Server
by Kathi Kellenberger Clayton GroomExpert T-SQL Window Functions in SQL Server takes you from any level of knowledge of windowing functions and turns you into an expert who can use these powerful functions to solve many T-SQL queries. Replace slow cursors and self-joins with queries that are easy to write and fantastically better performing, all through the magic of window functions. First introduced in SQL Server 2005, window functions came into full blossom with SQL Server 2012. They truly are one of the most notable developments in SQL in a decade, and every developer and DBA can benefit from their expressive power in solving day-to-day business problems. Begin using windowing functions like ROW_NUMBER and LAG, and you will discover more ways to use them every day. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster, they will be easier to write, and they will be easier to deconstruct and maintain and enhance in the future. Just knowing and using these functions is not enough. You also need to understand how to tune the queries. Expert T-SQL Window Functions in SQL Server explains clearly how to get the best performance. The book also covers the rare cases when older techniques are the best bet. Stop using cursors and self-joins to solve complicated queries. Become a T-SQL expert by mastering windowing functions. Teaches you how to use all the window functions introduced in 2005 and 2012. Provides real-world examples that you can experiment with in your own database. Explains how to get the best performance when using windowing functions. What you'll learn Create aggregations by defining sets of rows with the OVER clause. Calculate aggregates without losing the details. Rank and bucketize data for reporting purposes. Reduce and often eliminate self-joins. Reduce and often eliminate row-by-row cursor processing. Write simpler queries that perform with greater speed. Recognize situations when window functions make a difference. Who this book is for Expert T-SQL Window Functions in SQL Server is for the SQL Server database professionals who are ready to take on the biggest leap in query-writing expressiveness and performance to hit the SQL language in years. It's for developers and database administrators who may have heard about windowing functions, but who haven't had a chance to learn much about them. Expert T-SQL Window Functions in SQL Server is an excellent way for database professionals to get up to speed on these functions and put their benefits to work. Table of Contents 1. Looking through the Window 2. Discovering Ranking Functions 3. Aggregating with Window Functions 4. Tuning for Better Performance 5. Calculating Rolling and Running Aggregates 6. Adding Frames to the Window 7. Peaking at Other Rows 8. Understanding Statistical Functions 9. The Future of Window Functions
Expert T-SQL Window Functions in SQL Server 2019: The Hidden Secret to Fast Analytic and Reporting Queries
by Kathi Kellenberger Clayton Groom Ed PollackBecome an expert who can use window functions to solve T-SQL query problems. Replace slow cursors and self-joins with queries that are easy to write and perform better. This new edition provides expanded examples, including a chapter from the world of sports, and covers the latest performance enhancements through SQL Server 2019. Window functions are useful in analytics and business intelligence reporting. They came into full blossom with SQL Server 2012, yet they are not as well known and used as often as they ought to be. This group of functions is one of the most notable developments in SQL, and this book shows how every developer and DBA can benefit from their expressive power in solving day-to-day business problems. Once you begin using window functions, such as ROW_NUMBER and LAG, you will discover many ways to use them. You will approach SQL Server queries in a different way, thinking about sets of data instead of individual rows. Your queries will run faster, be easier to write, and easier to deconstruct, maintain, and enhance in the future.Just knowing and using these functions is not enough. You also need to understand how to tune the queries. Expert T-SQL Window Functions in SQL Server clearly explains how to get the best performance. The book also covers the rare cases when older techniques are the best bet.What You Will LearnSolve complex query problems without cumbersome self-joins that run slowly and are difficult to readCreate sliding windows in a result set for computing such as running totals and moving averagesReturn aggregate and detail data simultaneously from the same SELECT statementCompute lag and lead and other values that access data from multiple rows in a result setUnderstand the OVER clause syntax and how to control the windowAvoid framing errors that can lead to unexpected resultsWho This Book Is For Anyone who writes T-SQL queries, including database administrators, developers, business analysts, and data scientists. Before reading this book, you should understand how to join tables, write WHERE clauses, and build aggregate queries.
Expert Twisted: Event-driven And Asynchronous Programming With Python
by Mark Williams Cory Benfield Brian Warner Moshe Zadka Dustin Mitchell Kevin Samuel Pierre TardyExplore Twisted, the Python-based event-driven networking engine, and review several of its most popular application projects. It is written by community leaders who have contributed to many of the projects covered, and share their hard-won insights and experience.Expert Twisted starts with an introduction to event-driven programming, explaining it in the context of what makes Twisted unique. It shows how Twisted's design emphasizes testability as a solution to common challenges of reliability, debugging, and start-to-finish causality that are inherent in event-driven programming. It also explains asynchronous programming, and the importance of functions, deferreds, and coroutines. It then uses two popular applications, treq and klein, to demonstrate calling and writing Web APIs with Twisted.The second part of the book dives into Twisted projects, in each case explaining how the project fits into the Twisted ecosystem and what it does, and offers several examples to bring readers up to speed, with pointers to additional resources for more depth. Examples include using Twisted with Docker, as a WSGI container, for file sharing, and more.What You'll LearnIntegrate Twisted and asyncio using adaptersAutomate software build, test, and release processes with BuildbotCreate clients and servers with AutobahnTransfer files with Magic WormholeDistribute cloud-based file storage with Tahoe LAFSUnderstand HTTP/2 with Python and TwistedSupport for asynchronous tasks using Django ChannelsWho This Book Is ForReaders should have some Python experience and understand the essentials of containers and protocols, but need not be familiar with Twisted or the associated projects covered in the book.
Expertise at Work: Current and Emerging Trends
by Marie-Line Germain Robin S. GrenierExpertise, which combines knowledge, years of experience in one domain, problem-solving skills, and behavioral traits, is a valuable resource for organizations. To understand the diverse picture of expertise in the workplace, this book offers scholars and scholar-practitioners a comprehensive assessment of the development of human expertise in organizations. Using contemporary perspectives across a broad range of domains, contributors offer readers various professional perspectives including veterans, education, sports, and information technology. The book also describes how researchers and practitioners can address practical problems related to the development, redevelopment, and sustainability of expertise. Finally, the book puts specific emphasis on the emerging trends in the study and practice of expertise in organizations, including the use of artificial intelligence.
Explainable AI (XAI) for Sustainable Development: Trends and Applications
by Seifedine Kadry Rajesh Kumar Dhanaraj Ravi Shekhar Tiwari Lakshmi D.This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain.• Focuses on virtual machine placement and migration techniques for cloud data centres• Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services• Includes application of placement techniques for quality of service, performance, and reliability improvement• Explores data centre resource management, load balancing and orchestration using machine learning techniques• Analyses dynamic and scalable resource scheduling with a focus on resource managementThe reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.
Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python
by Pradeepta MishraUnderstand how to use Explainable AI (XAI) libraries and build trust in AI and machine learning models. This book utilizes a problem-solution approach to explaining machine learning models and their algorithms. The book starts with model interpretation for supervised learning linear models, which includes feature importance, partial dependency analysis, and influential data point analysis for both classification and regression models. Next, it explains supervised learning using non-linear models and state-of-the-art frameworks such as SHAP values/scores and LIME for local interpretation. Explainability for time series models is covered using LIME and SHAP, as are natural language processing-related tasks such as text classification, and sentiment analysis with ELI5, and ALIBI. The book concludes with complex model classification and regression-like neural networks and deep learning models using the CAPTUM framework that shows feature attribution, neuron attribution, and activation attribution. After reading this book, you will understand AI and machine learning models and be able to put that knowledge into practice to bring more accuracy and transparency to your analyses.What You Will LearnCreate code snippets and explain machine learning models using PythonLeverage deep learning models using the latest code with agile implementationsBuild, train, and explain neural network models designed to scaleUnderstand the different variants of neural network models Who This Book Is ForAI engineers, data scientists, and software developers interested in XAI
Explainable AI Within the Digital Transformation and Cyber Physical Systems: XAI Methods and Applications
by Moamar Sayed-MouchawehThis book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions.Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems;Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems;Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Explainable AI and Blockchain for Secure and Agile Supply Chains: Enhancing Transparency, Traceability, and Accountability
by Narasimha Rao Vajjhala Rajasekhara Mouly Potluri Ajay Kumar Sharma Rakshit KothariThis book examines the transformative potential of integrating explainable artificial intelligence (XAI) and blockchain technology in modern supply chain management.It explores how these innovative technologies address pressing challenges such as data transparency, traceability, fraud prevention, and operational efficiency in complex global supply chains. With detailed analyses, case studies, and real-world applications, these chapters provide insights into leveraging XAI to demystify AI decision-making and blockchain, ensuring data security and decentralized accountability. Key topics include sustainable practices, smart contract automation, and human-centric approaches to enhancing trust and collaboration among stakeholders.This comprehensive volume serves as a valuable resource for academics, industry leaders, and policymakers seeking to harness cutting-edge technologies for building resilient and transparent supply chains.
Explainable AI and Other Applications of Fuzzy Techniques: Proceedings of the 2021 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2021 (Lecture Notes in Networks and Systems #258)
by Vladik Kreinovich Julia Rayz Victor Raskin Scott DickThis book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques. This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general.
Explainable AI for Cybersecurity
by Prabhat Mishra Zhixin PanThis book provides a comprehensive overview of security vulnerabilities and state-of-the-art countermeasures using explainable artificial intelligence (AI). Specifically, it describes how explainable AI can be effectively used for detection and mitigation of hardware vulnerabilities (e.g., hardware Trojans) as well as software attacks (e.g., malware and ransomware). It provides insights into the security threats towards machine learning models and presents effective countermeasures. It also explores hardware acceleration of explainable AI algorithms. The reader will be able to comprehend a complete picture of cybersecurity challenges and how to detect them using explainable AI. This book serves as a single source of reference for students, researchers, engineers, and practitioners for designing secure and trustworthy systems.
Explainable AI for Education: Recent Trends and Challenges (Information Systems Engineering and Management #19)
by Álvaro Rocha Soumi Dutta Sonali Vyas Tanu Singh“Explainable AI for Education: Recent Trends and Challenges” is a comprehensive exploration of the intersection between artificial intelligence (AI) and education. In this book, we delve into the critical need for transparency and interpretability in AI systems deployed within educational contexts. Key Themes Understanding AI in Education: We provide a concise overview of AI techniques commonly used in educational settings, including recommendation systems, personalized learning, and assessment tools. Readers will gain insights into the potential benefits and risks associated with AI adoption in education. The Black-Box Problem: AI models often operate as “black boxes,” making it challenging to understand their decision-making processes. We discuss the implications of this opacity and emphasize the importance of explainability. Explainable AI (XAI) Techniques: From rule-based approaches to neural network interpretability, we explore various methods for making AI models more transparent. Examples and case studies illustrate how XAI can enhance educational outcomes. Ethical Considerations: As AI becomes more integrated into education, ethical dilemmas arise. We address issues related to bias, fairness, and accountability, emphasizing responsible AI practices. Future Directions: Our book looks ahead, considering the evolving landscape of AI and its impact on education. We propose research directions and practical steps to promote XAI adoption in educational institutions.
Explainable AI for Evolutionary Computation (Natural Computing Series)
by Anna V. Kononova Niki Van SteinThis book explores the intersection between explainable artificial intelligence (XAI) and evolutionary computation (EC). In recent years, the fields of XAI and EC have emerged as vital areas of study within the broader domain of artificial intelligence and computational intelligence. XAI seeks to address the pressing demand for transparency and interpretability in AI systems, enabling their decision-making processes to be scrutinised and trusted. Meanwhile, EC offers robust solutions to complex optimisation problems across diverse and challenging domains, drawing upon the principles of natural evolution. While each field has made significant contributions independently, their intersection remains an underexplored area rich with transformative potential. This book charts a path towards advancing computational systems that are transparent, reliable, and ethically sound. It aims to bridge the gap between XAI and EC by presenting a comprehensive exploration of methodologies, applications and case studies that highlight the synergies between these fields. This book will serve as both a resource and an inspiration, encouraging researchers and practitioners within XAI and EC, as well as those from adjacent disciplines, to collaborate and drive the development of intelligent computational systems that are not only powerful but also inherently trustworthy.
Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions
by Michael Munn David PitmanMost intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does.Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced machine learning engineers and data scientists will learn hands-on how these techniques work so that you'll be able to apply these tools more easily in your daily workflow.This essential book provides:A detailed look at some of the most useful and commonly used explainability techniques, highlighting pros and cons to help you choose the best tool for your needsTips and best practices for implementing these techniquesA guide to interacting with explainability and how to avoid common pitfallsThe knowledge you need to incorporate explainability in your ML workflow to help build more robust ML systemsAdvice about explainable AI techniques, including how to apply techniques to models that consume tabular, image, or text dataExample implementation code in Python using well-known explainability libraries for models built in Keras and TensorFlow 2.0, PyTorch, and HuggingFace
Explainable AI in Health Informatics (Computational Intelligence Methods and Applications)
by Patrick Siarry Mayuri Mehta Rajanikanth AluvaluThis book provides a comprehensive review of the latest research in the area of explainable artificial intelligence (XAI) in health informatics. It focuses on how explainable AI models can work together with humans to assist them in decision-making, leading to improved diagnosis and prognosis in healthcare. This book includes a collection of techniques and systems of XAI in health informatics and gives a wider perspective about the impact created by them. The book covers the different aspects, such as robotics, informatics, drugs, patients, etc., related to XAI in healthcare. The book is suitable for both beginners and advanced AI practitioners, including students, academicians, researchers, and industry professionals. It serves as an excellent reference for undergraduate and graduate-level courses on AI for medicine/healthcare or XAI for medicine/healthcare. Medical institutions can also utilize this book as reference material and provide tutorials to medical professionals on how the XAI techniques can contribute to trustworthy diagnosis and prediction of the diseases.
Explainable AI in Healthcare and Medicine: Building a Culture of Transparency and Accountability (Studies in Computational Intelligence #914)
by David L. Buckeridge Arash Shaban-Nejad Martin MichalowskiThis book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.
Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine (Analytics and AI for Healthcare)
by Mehul S Raval Mohendra Roy Tolga Kaya Rupal KapdiThis book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artificial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefit readers in the following ways: Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care Investigates bridges between computer scientists and physicians being built with XAI Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent Initiates discussions on human-AI relationships in health care Unites learning for privacy preservation in health care