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Scientific Computation: Python Hacking for Math Junkies by Shapiro, Bruce E
US $10.26
ApproximatelyEUR 8.86
Condition:
Good
A book that has been read, but is in good condition. Minimal damage to the book cover eg. scuff marks, but no holes or tears. If this is a hard cover, the dust jacket may be missing. Binding has minimal wear. The majority of pages are undamaged with some creasing or tearing, and pencil underlining of text, but this is minimal. No highlighting of text, no writing in the margins, and no missing pages. See the seller’s listing for full details and description of any imperfections.
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Located in: Columbia, Missouri, United States
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Estimated between Fri, 8 Aug and Thu, 14 Aug to 94104
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eBay item number:205651396988
Item specifics
- Condition
- 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
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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One Planet Books
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- c***i (293)- Feedback left by buyer.Past monthVerified purchaseBuen precio y rapidez en el envío. Gracias.
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