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Autor(en): 
  • Bruce E. Shapiro
  • Scientific Computation: Python Hacking for Math Junkies 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Januar 2015  
    Genre:  EDV / Informatik 
     
    COMPUTERS / Programming Languages / Python / Mathematics / MATHEMATICS / Numerical Analysis / Programmier- und Skriptsprachen, allgemein
    ISBN:  9780692366936 
    EAN-Code: 
    9780692366936 
    Verlag:  Touchladybirdlucky Studios 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D 29 mm 
    Gewicht:  953 gr 
    Seiten:  556 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    There is a newer edition (ISBN 978-1725894662) of this book that actually covers Python 3.6.

    This is a book about hacking, but not just any kind of hacking. It is about mathematical hacking, or scientific computing. If you like math and want to use computers to do math or solve mathematical problems, then this book is the for you.

    This is version 3, which includes over 80 additional pages, with extensive additions on Python classes, iPython with jupyter notebooks, magic functions, random numbers, and probability and statistics. The emphasis throughout the text is on programming in the iPython notebook. Version 3.0.3 (2017) is revised and corrected.

    Part I gives an introduction to programming, the Python shell, and using iPython notebooks.

    Part II gives a thorough tour of the Python language. Topics include data types, simple statements, assignments, conditionals, loops, list comprehension, sorting, Numpy, pyplot, using dictionaries, functions, classes, functional programs, lambda functions, and recursion.

    Part III gives applications, including probability and statistics, and topics from machine learning such as clustering, linear regression, logistic regression and principal component analysis. Other topics include image analysis, the singular value decomposition, solving initial value problems, discrete systems, fractals, estimating pi, geographic maps, and satellite orbit analysis.

    Over 300 problems are included that can be used for student programming projects.

    No programming background required. Some basic understanding of math through calculus expected for the applications.

      
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