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  • Sách/Book

  • Enterprise digital reliability : building security, usability, and digital trust

    • Authors: Manoj Kuppam (2024)

  • Part of author Saurav Bhattacharyas trilogy that covers the essential pillars of digital ecosystemssecurity, reliability, and usabilitythis book tackles the challenges of achieving high reliability in complex systems and provides strategies to overcome these obstacles. Youll start by reviewing the pivotal role of reliability in establishing the foundation of digital trust, essential for the sustainable growth of digital ecosystems.
  • Sách/Book

  • Wi-fi 7 : principles, technology, and applications

    • Authors: Gang Cheng (2025)

  • By reading this book, you will not only gain insights into the state-of-the-art of Wi-Fi 7 technology, but also develop a deep understanding of the origins, the process of developing Wi-Fi 7 products, various applications and solutions where Wi-Fi 7 can be utilized, and the current state of the industry in relation to Wi-Fi 7 technology compared to the other wireless technologies.
  • Sách/Book

  • Events design and experience

    • Authors: Graham Berridge (2007)

  • For The first rime Events Design and Experience draws together the relationship between event design and the experience of consumers and participants. It explores and analyses the event experience of the individual and how this can be 'controlled' by design
  • Sách/Book

  • Essential Data Analytics, Data Science, and AI A Practical Guide for a Data-Driven World

    • Authors: Maxine Attobrah (2025)

  • This book is your thorough guide to learning these innovative fields, designed to make the learning practical and engaging. The book starts by introducing data analytics, data science, and artificial intelligence. It illustrates real-world applications, and, it addresses the ethical considerations tied to AI.
  • Sách/Book

  • Advances in machine learning and big data analytics. I : ICMLBDA 2023, NIT Arunachal Pradesh, India, May 29-30

    • Authors: Ashokkumar Patel (2025)

  • The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field.
  • Sách/Book

  • Introduction to artificial intelligence

    • Authors: Wolfgang Ertel (2025)

  • This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning.
  • Sách/Book

  • Functional analysis for the applied mathematician

    • Authors: Todd Arbogast (2025)

  • This is a self-contained volume providing a rigorous introduction to functional analysis and its applications. Students from mathematics, science, engineering, and certain social science and interdisciplinary programs will benefit from the material. It is accessible to graduate and advanced undergraduate students with a solid background in undergraduate mathematics and an appreciation of mathematical rigor.
  • Sách/Book

  • Optimization, Discrete Mathematics and Applications to Data Sciences

    • Authors: Ashkan Nikeghbali (2025)

  • This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.