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Results 1331-1340 of 1529 (Search time: 0.349 seconds).
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  • Sách/Book

  • Practical machine learning : a beginner's guide with ethical insights

    • Authors: Ally S. Nyamawe (2025)

  • The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field. This is a core resource for students and instructors of machine learning and data science looking for beginner-friendly material which offers real-world applications and takes ethical discussions into account
  • Sách/Book

  • Data Analysis for Business Decisions : Case Studies in Excel, R, and ChatGPT

    • Authors: Andres Fortino (2025)

  • This book provides a comprehensive, hands-on guide to mastering the essential techniques and tools that empower business analysts to transform raw data into actionable insights. Packed with practical exercises and real-world case studies, this book focuses on applying statistical methods across the most widely used tools, including Excel, R, Python, and generative AI platforms like ChatGPT.
  • Sách/Book

  • Artificial Intelligence: Principles and Practice

    • Authors: George F. Luger (2025)

  • This book provides a complete introduction to Artificial Intelligence, covering foundational computational technologies, mathematical principles, philosophical considerations, and engineering disciplines essential for understanding AI.
  • Sách/Book

  • Digital twins and cybersecurity : safeguarding the future of connected systems

    • Authors: Palanichamy Naveen (2025)

  • This book explores the convergence of digital twins and cybersecurity, offering insights, strategies, and best practices for safeguarding connected systems. It examines the definition, evolution, types, and applications of digital twins across industries like manufacturing, healthcare, and transportation.
  • Sách/Book

  • Deep learning applications in operations research

    • Authors: Aryan Chaudhary (2025)

  • Case studies look at how to streamline operations and unearth data to make better business decisions. The concepts presented in this book can bring about and guide unique research directions to the future application of AI enabled technologies
  • Sách/Book

  • Measure and integration : an introduction

    • Authors: Satya N. Mukhopadhyay (2025)

  • It acts as a pivotal link bridging the Riemann integral and the Lebesgue integral, with a primary focus on tracing the evolution of measure and integration from their historical roots. A distinctive feature of the book is meticulous guidance, providing a step-by-step journey through the subject matter, thus rendering complex concepts more accessible to beginners
  • Sách/Book

  • Java 23 for absolute beginners : learn the fundamentals of Java programming

    • Authors: Iuliana Cosmina (2024)

  • This book is a complete Java guide, covering the following topics: setting up a development environment, programming concepts and well-known programming principles, writing Java code following industry-specific design patterns and coding conventions, executing it, debugging, testing, documenting it and even using specialized tools such as IntelliJ IDEA for writing Java code, Maven for building, JUnit Jupiter for testing, and in-memory and Docker-hosted databases or data storage
  • Sách/Book

  • Abstract algebra via numbers

    • Authors: Lars Tuset (2025)

  • This book is a concise, self-contained treatise on abstract algebra with an introduction to number theory, where students normally encounter rigorous mathematics for the first time. The authors build up things slowly, by explaining the importance of proofs. Number theory with its focus on prime numbers is then bridged via complex numbers and linear algebra, to the standard concepts of a course in abstract algebra, namely groups, representations, rings, and modules.