Scientific Computing with Python: High-performance scientific computing with Num

Description: Scientific Computing with Python by Claus Fuhrer, Olivier Verdier, Jan Erik Solem Python is an efficient tool for coupling scientific computing and mathematics. This book teaches you how to use it for linear algebra, arrays, plotting, iterating, functions, and polynomials. Youll explore task automation and understand essential math concepts and algorithms along with integrations for faster computation in scientific computing. FORMAT Paperback CONDITION Brand New Publisher Description Leverage this example-packed, comprehensive guide for all your Python computational needsKey FeaturesLearn the first steps within Python to highly specialized conceptsExplore examples and code snippets taken from typical programming situations within scientific computing.Delve into essential computer science concepts like iterating, object-oriented programming, testing, and MPI presented in strong connection to applications within scientific computing.Book DescriptionPython has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python.This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. Youll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. Youll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations.By the end of this Python book, youll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.What you will learnUnderstand the building blocks of computational mathematics, linear algebra, and related Python objectsUse Matplotlib to create high-quality figures and graphics to draw and visualize resultsApply object-oriented programming (OOP) to scientific computing in PythonDiscover how to use pandas to enter the world of data processingHandle exceptions for writing reliable and usable codeCover manual and automatic aspects of testing for scientific programmingGet to grips with parallel computing to increase computation speedWho this book is forThis book is for students with a mathematical background, university teachers designing modern courses in programming, data scientists, researchers, developers, and anyone who wants to perform scientific computation in Python. Author Biography Claus Fuhrer is a professor of scientific computations at Lund University, Sweden. He has an extensive teaching record that includes intensive programming courses in numerical analysis and engineering mathematics across various levels in many different countries and teaching environments. Claus also develops numerical software in research collaboration with industry and received Lund Universitys Faculty of Engineering Best Teacher Award in 2016.Jan Erik Solem is a Python enthusiast, former associate professor, and computer vision entrepreneur. He co-founded several computer vision startups, most recently Mapillary, a street imagery computer vision company, and has worked in the tech industry for two decades. Jan Erik is a World Economic Forum technology pioneer and won the Best Nordic Thesis Award 2005-2006 for his dissertation on image analysis and pattern recognition. He is also the author of "Programming Computer Vision with Python" (OReilly 2012).Olivier Verdier began using Python for scientific computing back in 2007 and received a PhD in mathematics from Lund University in 2009. He has held post-doctoral positions in Cologne, Trondheim, Bergen, and Ume and is now an associate professor of mathematics at Bergen University College, Norway. Table of Contents Table of ContentsGetting StartedVariables and Basic TypesContainer TypesLinear Algebra – ArraysAdvanced Array ConceptsPlottingFunctionsClassesIteratingSeries and Dataframes - Working With PandasCommunication by a Graphical User InterfaceError and Exception HandlingNamespaces, Scopes, and ModulesInput and OutputTestingSymbolic Computations - SymPyInteracting with the Operating SystemPython for Parallel ComputingComprehensive Examples Details ISBN1838822321 Author Jan Erik Solem Publisher Packt Publishing Limited Year 2021 ISBN-10 1838822321 ISBN-13 9781838822323 Edition 2nd Format Paperback Imprint Packt Publishing Limited Place of Publication Birmingham Country of Publication United Kingdom Pages 392 Subtitle High-performance scientific computing with NumPy, SciPy, and pandas AU Release Date 2021-07-29 NZ Release Date 2021-07-29 Edition Description 2nd Revised edition Publication Date 2021-07-29 DEWEY 005.133 Audience Professional & Vocational UK Release Date 2021-07-29 We've got this At The Nile, if you're looking for it, we've got it. 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