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Scientific Computation: Python Hacking for Math Junkies by Shapiro, Bruce E
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Scientific Computation: Python Hacking for Math Junkies by Shapiro, Bruce E
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Aug 07, 00:21Aug 07, 00:21
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Scientific Computation: Python Hacking for Math Junkies by Shapiro, Bruce E

US $10.26
ApproximatelyRM 43.38
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    eBay item number:205651396988

    Item specifics

    Condition
    Good: A book that has been read but is in good condition. Very minimal damage to the cover including ...
    Book Title
    Scientific Computation: Python Hacking for Math Junkies
    ISBN
    9780692366936

    About this product

    Product Identifiers

    Publisher
    Sherwood Forest Books
    ISBN-10
    0692366938
    ISBN-13
    9780692366936
    eBay Product ID (ePID)
    208648817

    Product Key Features

    Number of Pages
    554 Pages
    Language
    English
    Publication Name
    Scientific Computation : Python Hacking for Math Junkies
    Publication Year
    2015
    Subject
    Programming Languages / Python
    Type
    Textbook
    Author
    Bruce Shapiro
    Subject Area
    Computers
    Format
    Trade Paperback

    Dimensions

    Item Height
    1.2 in
    Item Weight
    41.5 Oz
    Item Length
    10 in
    Item Width
    7 in

    Additional Product Features

    Intended Audience
    Trade
    Synopsis
    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 additionson 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 usingiPython 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, andtopics from machine learning such as clustering, linear regression,logistic regression and principal component analysis. Other topics includeimage analysis, the singular value decomposition, solving initial value problems, discrete systems, fractals, estimating pi, geographicmaps, 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 throughcalculus expected for the applications., 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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