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Results 111-120 of 132 (Search time: 0.146 seconds).
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  • Sách/Book

  • Applied linear statistical models.

    • Authors: Michael H. Kutner (2005)

  • A text and reference on statistical modeling, this work includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. It provides a use of computing and graphical analysis.
  • Sách/Book

  • Sams Teach Yourself C++ in 21 Days

    • Authors: Jesse Liberty; Bradley Jones (2004)

  • This is an excellent hands-on guide for the beginning programmer. Packed with examples of syntax and detailed analysis of code, fundamentals such as managing I/O, loops, arrays and creating C++ applications are all covered in the 21 easy-to-follow lessons.
  • Sách/Book

  • AI in the financial markets : new algorithms and solutions

    • Authors: Federico Cecconi (2023)

  • This book is divided into two parts, the first of which describes AI as we know it today, in particular the Fintech-related applications. In turn, the second part explores AI models in financial markets: both regarding applications that are already available (e.g. the blockchain supply chain, learning through big data, understanding natural language, or the valuation of complex bonds) and more futuristic solutions (e.g. models based on artificial agents that interact by buying and selling stocks within simulated worlds).
  • 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

  • Visualization for artificial intelligence

    • Authors: Shixia Liu (2025)

  • This book: Covers visual analytics deployments in all stages of machine learning model building Demonstrates how visual analytics enhances the explainability and implementation of XAI Explores techniques to improve explainable AI through visual analysis