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  • Sách/Book


  • Authors: Crista Arangala (2025)

  • This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition and connections to differential equations

  • Sách/Book


  • Authors: Bharat Bhushan (2025)

  • This book is an essential resource on the impact of AI in medical systems, helping readers stay ahead in the modern era with cutting-edge solutions, knowledge, and real-world case studies. Wellness Management Powered by AI Technologies explores the intricate ways machine learning and the Internet of Things (IoT) have been woven into the fabric of healthcare solutions.

  • Sách/Book


  • Authors: Ronald T. Kneusel (2024)

  • In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms

  • Sách/Book


  • Authors: Mark J. DeBonis. (2025)

  • A Beginner's Guide to Mathematical Proof prepares mathematics majors for the transition to abstract mathematics, as well as introducing a wider readership of quantitative science students, such as engineers, to the mathematical structures underlying more applied topics

  • Sách/Book


  • 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.