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Morgan Kaufmann

    • Mastering Cloud Computing

      • 2nd Edition
      • March 1, 2026
      • Rajkumar Buyya + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 0 4 3 5 1
      • eBook
        9 7 8 0 4 4 3 4 0 4 3 6 8
      Mastering Cloud Computing: Foundations and Applications Programming, Second Edition serves as a comprehensive introduction for readers seeking to develop applications in the ever-evolving world of cloud computing. As technology advances, applications are no longer confined to a single machine but instead operate from virtual servers, accessible globally at any time. This book equips aspiring developers with the essential tools and knowledge to create effective cloud-based applications. Beyond the foundational principles, the book delves into distributed and parallel computing, providing in-depth coverage of virtualization, thread programming, task programming, and map-reduce techniques.It also addresses the development of applications for various cloud architectures, highlighting industrial platforms and critical security considerations. To reinforce learning, the text integrates real-world case studies, practical examples, hands-on exercises, and lab activities throughout, allowing readers to apply concepts directly and build their expertise effectively.

    • Full-Stack Web Development from the Ground Up

      • 1st Edition
      • February 19, 2026
      • Christopher D Hundhausen
      • English
      • Paperback
        9 7 8 0 3 2 3 9 1 8 8 4 8
      • eBook
        9 7 8 0 3 2 3 9 1 9 5 4 8
      Full-Stack Development from the Ground Up: Principles, Practices, and Technologies addresses the growing need for a comprehensive upper-division computer science textbook that provides in-depth treatment of full-stack web development using the modern web development technologies that students are likely to encounter in industry. Professional full-stack web developers who are capable of developing both the front-end user interfaces and back-end databases and services for dynamic websites are in high demand. The book begins by laying a foundation in HTML, CSS and JavaScript—the building blocks of client-side web development.It then explores one particular web development stack in detail: MERN, which stands for MongoDB, Express.js, React.js and Node.js. Together, these four technologies provide powerful support for full-stack web development in a single programming language—JavaScript. The crucial final step in the web development process is deploying apps to a server, so users can interact with them. This book simplifies deployment by focusing on just one web deployment environment: Amazon Web Services (AWS), and only those AWS tools that are absolutely necessary to deploy MERN applications.

    • Tcl/Tk

      • 4th Edition
      • February 15, 2026
      • Clif Flynt
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 5 5 6 3
      • eBook
        9 7 8 0 4 4 3 2 6 5 5 7 0
      Tcl/Tk: A Developer's Guide, Fourth Edition is an essential resource for computer professionals, from systems administrators to programmers. It covers new Tcl features, expanded Tcl-OO coverage, web technology using Rivet and SQLite, and AI integration with AWS. The book also delves into Tcl's standard tools, multi-faceted nature, and extensibility, making it ideal for developing GUIs, client/server middleware, and web applications. Readers will quickly learn to code in Tcl and extend its capabilities with the inclusion of numerous code examples and case studies.The updated edition includes over 150 pages on the latest Tcl extensions, proven techniques, and tools for effective programming. Extensive code snippets and online tutorials enhance understanding, while case studies provide practical insights. The book also discusses Tcl's role as the hidden "secret sauce" in commercial applications, highlighting its graphics and control infrastructure. With a vibrant user community and evolving API, Tcl/Tk remains a powerful and versatile programming platform for both beginners and experienced programmers.

    • Digital Transformation in Artificial Systems

      • 1st Edition
      • February 1, 2026
      • Mirko Farina + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 2 9 6 4 7
      • eBook
        9 7 8 0 4 4 3 3 2 9 6 5 4
      Digital Transformation in Artificial Systems: Engineering Requirements and Political, Economic, and Philosophical Challenges is a groundbreaking work that scrutinizes the engineering necessities, political ramifications, and ethical dilemmas associated with the digital transformation, particularly within Artificial Systems. This transformative concept, which involves leveraging technological advancements to redefine operations and processes, is explored through an interdisciplinary lens, incorporating insights from computer science, engineering, philosophy, economy, and sociology. The book advocates for an inclusive digital transformation that addresses the global digital divide and promotes cooperation in digitization, industrialization, and innovation.It emphasizes the importance of understanding ethical challenges and developing fair policies that enhance human flourishing, social harmony, and moral good. The interdisciplinary framework provided by the authors offers essential insights into the forthcoming AI revolution and its societal impact.

    • Essentials of Big Data Analytics

      • 1st Edition
      • February 1, 2026
      • Pallavi Chavan + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 5 2 0 6 2
      • eBook
        9 7 8 0 4 4 3 4 5 2 0 7 9
      Essentials of Big Data Analytics: Applications in R and Python is a comprehensive guide that demystifies the complex world of big data analytics, blending theoretical concepts with hands-on practices using the Python and R programming languages and MapReduce framework. This book bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of big data. Essentials of Big Data Analytics is designed to provide a comprehensive resource for readers looking to deepen their understanding of Big Data analytics, particularly within a computer science, engineering, and data science context. By bridging theoretical concepts with practical applications, the book emphasizes hands-on learning through exercises and tutorials, specifically utilizing R and Python. Given the growing role of Big Data in industry and scientific research, this book serves as a timely resource to equip professionals with the skills needed to thrive in data-driven environments.

    • Learning-Driven Game Theory for AI

      • 1st Edition
      • February 1, 2026
      • Mehdi Salimi + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 3 8 5 2 3
      • eBook
        9 7 8 0 4 4 3 4 3 8 5 3 0
      Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science. In this book, the authors bridge the gap between traditional game theory and its modern applications in artificial intelligence (AI) and related technological fields. The dynamic nature of contemporary problems in robotics, cybersecurity, machine learning, and multi-agent systems requires game-theoretic solutions that go beyond classical methods. The book delves into the rapidly growing intersection of pursuit differential games and AI, focusing on how these advanced game-theoretic models can be applied to modern AI systems, making it an indispensable resource for both academics and professionals. The book also provides a variety of applications demonstrating the practical integration of AI and game theory across various disciplines, such as autonomous systems, federated learning, and distributed decision-making frameworks. The book also explores the use of game theory in reinforcement learning, swarm intelligence, multi-agent coordination, and cybersecurity. These are critical areas where AI and dynamic games converge. Each chapter covers a different facet of dynamic games, offering readers a comprehensive yet focused exploration of topics such as differential and discrete-time games, evolutionary dynamics, and repeated and stochastic games. The absence of static games ensures a concentrated focus on the dynamic, evolving problems that are most relevant today.

    • Computer Animation

      • 4th Edition
      • January 20, 2026
      • Andrew Hogue + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 3 5 1 2 5
      • eBook
        9 7 8 0 4 4 3 1 3 5 1 3 2
      Computer Animation: Algorithms and Techniques, Fourth Edition surveys computer algorithms and programming techniques for specifying and generating motion for graphical objects, that is, computer animation. It is primarily concerned with three-dimensional (3D) computer animation. In this edition, the most current techniques are covered along with the theory and high-level computation that have earned the book a reputation as the best technically oriented animation resource. As in previous editions, the book addresses practical issues, provides accessible techniques, and offers straightforward implementations.

    • Observing the User Experience

      • 3rd Edition
      • January 1, 2026
      • Elizabeth Goodman + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 1 5 5 6 9 1
      • eBook
        9 7 8 0 1 2 8 1 8 9 2 7 6
      Observing the User Experience: A Practitioner's Guide to User Research, Third Edition helps readers bridge the gap to understand what users want and need from their product. Filled with real-world experience and a wealth of practical information, the book presents a complete toolbox of techniques to help designers, developers, and other stakeholders see through the eyes of their users. Sections discuss the benefits of end-user research and the ways it fits into the development of useful, desirable, and successful products and present techniques for understanding people’s needs, desires, and abilities, providing a basis for developing better products, whether Web, software, or mobile-based.Final chapters explain the communication and application of research results.

    • Challenges and Applications of Generative Large Language Models

      • 1st Edition
      • January 1, 2026
      • Anitha S. Pillai + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 5 9 2 1
      • eBook
        9 7 8 0 4 4 3 3 3 5 9 3 8
      Large Language Models (LLMs) are a form of generative AI, based on Deep Learning, that rely on very large textual datasets, and are composed of hundreds of millions (or even billions) of parameters. LLMs can be trained and then refined to perform several NLP tasks like generation of text, summarization, translation, prediction, and more. Challenges and Applications of Generative Large Language Models assists readers in understanding LLMs, their applications in various sectors, challenges that need to be encountered while developing them, open issues, and ethical concerns. LLMs are just one approach in the huge set of methodologies provided by AI. The book, describing strengths and weaknesses of such models, enables researchers and software developers to decide whether an LLM is the right choice for the problem they are trying to solve. AI is the new buzzword, in particular Generative AI for human language (LLMs). As such, an overwhelming amount of hype is obfuscating and giving a distorted view about AI in general, and LLMs in particular. Thus, trying to provide an objective description of LLMs is useful to any person (researcher, professional, student) who is starting to work with human language. The risk, otherwise, is to forget the whole set of methodologies developed by AI in the last decades, sticking with only one model which, although very powerful, has known weaknesses and risks. Given the high level of hype around such models, Challenges and Applications of Generative Large Language Models (LLMs) enables readers to clarify and understand their scope and limitations.

    • Fundamentals of Statistics for Researchers and Data Analysts

      • 1st Edition
      • January 1, 2026
      • Shashi Chiplonkar + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 4 4 7 5 1 8
      • eBook
        9 7 8 0 4 4 3 4 4 7 5 2 5
      Fundamentals of Statistics for Researchers and Data Analysts explains statistical methods, and the assumptions and prerequisites for applying various analytical tools from an statistical point of view. Statistical analysis has become indispensable in almost all fields of science, business, industry and medicine, for evidence-based decision making and forecasting. However, due to lack of fundamental understanding of statistics, results of data analysis often remain inconclusive or erroneous. In addition, data analysts or even statistical advisers may not be familiar with the subject area of the data, leading to inaccurate application of statistical tools and interpretation of results. To address these issues, this book breaks down the concepts of statistics into accessible, practical explanations with real-world examples. The book is organized by first explaining what statistical thinking is and how one should proceed with formulating their question in terms of a statistical hypothesis. Then step by step, topics are explained in detail, including data generation by choice of proper study design, data collection methods, identifying outliers, methods of data analysis, and finally interpretation of results to help make the required decision. Essential statistical methods such as classification techniques, correlation analysis, regression models, probability distributions, model building and statistical tests of significance are explained with live datasets using Excel and SPSS. Fundamentals of Statistics for Researchers and Data Analysts instructs readers on the precise methodology of analyzing data and interpretation of statistical results to arrive at a valid conclusion. Readers can use the same methodology from the case studies given in the book for their own applications and research by replacing the variables in the examples with the variables from their own datasets. The book ensures that readers are well-prepared for data-driven roles in various sectors.

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