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Autor(en): 
  • Halidias Nikolaos
  • Linear Algebra With Python And Ai 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Vorankündigung
    Veröffentlichung:  ANGEKÜNDIGT (September 2027)  
    Genre:  Schulbücher 
     
    Algebra / COMPUTERS / Languages / Python / MATHEMATICS / Algebra / Linear / Programming & scripting languages# general / Programming and scripting languages# general
    ISBN:  9789819826988 
    EAN-Code: 
    9789819826988 
    Verlag:  World Scientific Publishing 
    Einband:  Gebunden  
    Sprache:  English  
    Seiten:  452 
    Bewertung: Keine Bewertung vor Veröffentlichung möglich.
    Inhalt:
    This book is a compelling and accessible introduction to linear algebra, ideal for learners and educators across mathematics, data science, engineering, and the physical sciences. It begins with core topics such as systems of linear equations, matrix operations, and Row-Reduced Echelon Form (RREF), and builds a coherent pathway toward advanced concepts like eigenvalues, inner product spaces, and singular value decomposition (SVD). With a clear pedagogical structure and consistent notation, the text supports both conceptual understanding and practical application.What sets this textbook apart is its seamless integration of theory and computation. Python (NumPy/SymPy) is used throughout to implement algorithms, visualize geometric ideas, and connect abstract mathematics to real-world problems. Carefully designed TikZ diagrams enhance geometric intuition, while applications such as least squares, data compression, and principal component analysis (PCA) demonstrate the relevance of linear algebra in modern fields. Integrated coding examples and computational tools encourage hands-on exploration and foster algorithmic thinking.Whether you're mastering Gaussian elimination, exploring the Rank-Nullity Theorem, or experimenting with Python notebooks, Linear Algebra with Python and AI offers a unified and forward-looking approach. With its dual emphasis on mathematical rigor and computational practice, this book equips students with the tools to navigate the mathematical foundations of today's data-driven world.

      



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