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  • Sách/Book

  • Driving 5G Mobile Communications with Artificial Intelligence towards 6G

    • Authors: Dragorad A. Milovanovic (2023)

  • Driving 5G Mobile Communications with Artificial Intelligence towards 6G is a moderate book with figures, tables, lists, MathML and formatting defined with structural markup. This book contains accessibility features such as a table of content, landmark, reading order, structural navigation, index, semantic structure, print page fidelity, in-text navigation links, and backlinks returning to the first in-text citation. Linked DOIs are provided, but are not uniquely identified.
  • Sách/Book

  • The thinking healthcare system : artificial intelligence and human equity

    • Authors: Dominique J. Monlezun (2023)

  • The Thinking Healthcare System: Artificial Intelligence and Human Equity is the first comprehensive book detailing the historical, global, and technical trends shaping the evolution of the modern healthcare system into its final form―an AI-driven thinking healthcare system, structured and functioning as a global digital health ecosystem.
  • Sách/Book

  • Convergence of cloud with AI for big data analytics : foundations and innovation

    • Authors: Danda B. Rawat (2023)

  • This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services. The 17 chapters of the book masterfully and comprehensively cover the intertwining concepts of artificial intelligence, cloud computing, and big data, all of which have recently emerged as the next-generation paradigms.
  • Sách/Book

  • All in on AI : how smart companies win big with artificial intelligenc

    • Authors: Thomas H. Davenport (2023)

  • If you're curious about the next phase in the implementation of artificial intelligence within companies, or if you're looking to adopt this powerful technology in a more robust way yourself, All-In on AI will give you a rare inside look at what the leading adopters are doing, while providing you with the tools to put AI at the core of everything you do.
  • Sách/Book

  • Deep Learning on Microcontrollers Learn How to Develop Embedded Al Applications Using TinyML

    • Authors: Atul Krishna Gupta (2023)

  • This book aims to increase accessibility to TinyML applications, particularly for professionals who lack the resources or expertise to develop and deploy them on microcontroller-based boards. The book starts by giving a brief introduction to Artificial Intelligence, including classical methods for solving complex problems. It also familiarizes you with the different ML model development and deployment tools, libraries, and frameworks suitable for embedded devices and microcontrollers.
  • Sách/Book

  • Diagnosis of neurological disorders based on deep learning techniques

    • Authors: Jyotismita Chaki (2023)

  • This book is based on deep learning approaches used for the diagnosis of neurological disorders, including basics of deep learning algorithms using diagrams, data tables, and practical examples, for diagnosis of neurodegenerative and neurodevelopmental disorders.
  • Sách/Book

  • System Design for Epidemics Using Machine Learning and Deep Learning

    • Authors: G. R. Kanagachidambaresan (2023)

  • This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis.
  • Sách/Book

  • AI for scientific discovery

    • Authors: Janna Hastings (2023)

  • AI for Scientific Discovery provides an accessible introduction to the wide-ranging applications of artificial intelligence technologies in scientific research and discovery across the full breadth of scientific disciplines. Artificial intelligence technologies support discovery science in multiple different ways. They support literature management and synthesis, allowing the wealth of what has already been discovered and reported on to be integrated and easily accessed. They play a central role in data analysis and interpretation - in the context of what is called 'data science'. AI is also helping to combat the reproducibility crisis in scientific research, by underpinning the discovery process with AI-enabled standards and pipelines, support the management of large-scale data and...