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Results 61-70 of 77 (Search time: 0.059 seconds).
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  • 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

  • Grokking Deep Reinforcement Learning

    • Authors: Miguel Morales (2021)

  • This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.
  • Sách/Book

  • Graphic design rules : 365 essential design dos and dont's

    • Authors: Sean Adams (2020)

  • 365 Design do's and don'ts, each presented with pithy accompanying text. A reference book and a primer, described in the foreword as both 'a guide to avoiding rookie mistakes' and 'a list of 'Oh yeah? We'll see about that!' challenges.
  • 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

  • Advancement of deep learning and its applications in object detection and recognition

    • Authors: Roohie Naaz Mir (2022)

  • The book describes every newly proposed novel solution but skips through the fundamentals so that readers can see the field's cutting edge more rapidly. Moreover, unlike prior object detection publications, this project analyses deep learning-based object identification methods systematically and exhaustively, and also gives the most recent detection solutions and a collection of noteworthy research trends.
  • 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.