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Autor(en): 
  • Heineman George
  • Pollice Gary
  • Selkow Stanley
  • Algorithms in a Nutshell, 2e 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  April 2016  
    Genre:  EDV / Informatik 
     
    Algorithms & data structures / algorithms and data structures / algorithms data structures Python Java C++ C pattern matching graphics search path finding / COMPUTERS / Programming / Algorithms
    ISBN:  9781491948927 
    EAN-Code: 
    9781491948927 
    Verlag:  O'Reilly 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 150 mm / D 21 mm 
    Gewicht:  538 gr 
    Seiten:  390 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. This updated edition of Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs—with just enough math to let you understand and analyze algorithm performance.

    With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate.

    With this book, you will:

    • Solve a particular coding problem or improve on the performance of an existing solution
    • Quickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to use
    • Get algorithmic solutions in C, C++, Java, and Python with implementation tips
    • Learn the expected performance of an algorithm, and the conditions it needs to perform at its best
    • Discover the impact that similar design decisions have on different algorithms
    • Learn advanced data structures to improve the efficiency of algorithms

      



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