{"product_id":"analysis-for-computer-scientists-foundations-methods-and-algorithms-9783319911540","title":"Analysis for Computer Scientists: Foundations, Methods, and Algorithms","description":"\u003cp\u003e • Author(s): Michael Oberguggenberger\u003cbr\u003e • Publisher: Springer\u003cbr\u003e • Publisher Imprint: Springer\u003cbr\u003e • BISAC: Data Science - General\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFrom the Back Cover\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThis easy-to-follow textbook\/reference presents a concise introduction to mathematical analysis from an algorithmic point of view, with a particular focus on applications of analysis and aspects of mathematical modelling. The text describes the mathematical theory alongside the basic concepts and methods of numerical analysis, enriched by computer experiments using MATLAB, Python, Maple, and Java applets. This fully updated and expanded new edition also features an even greater number of programming exercises.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTopics and features: \u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDescribes the fundamental concepts in analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives, integrals, and curves\u003c\/li\u003e\n\u003cli\u003eDiscusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations\u003c\/li\u003e\n\u003cli\u003ePresents tools from vector and matrix algebra in the appendices, together with further information on continuity\u003c\/li\u003e\n\u003cli\u003eIncludes added material on hyperbolic functions, curves and surfaces in space, second-order differential equations, and the pendulum equation \u003cb\u003e(NEW)\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eContains experiments, exercises, definitions, and propositions throughout the text\u003c\/li\u003e\n\u003cli\u003eSupplies programming examples in Python, in addition to MATLAB \u003cb\u003e(NEW)\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eProvides supplementary resources at an associated website, including Java applets, code source files, and links to interactive online learning material\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAddressing the core needs of computer science students and researchers, this clearly written textbook is an essential resource for undergraduate-level courses on numerical analysis, and an ideal self-study tool for professionals seeking to enhance their analysis skills.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDr. Michael Oberguggenberger\u003c\/b\u003e is a professor in the Unit of Engineering Mathematics at the University of Innsbruck, Austria. \u003cb\u003eDr. Alexander Ostermann\u003c\/b\u003e is a professor in the Department of Mathematics at the University of Innsbruck, Austria.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Paperback","offer_id":45276739895447,"sku":"9783319911540","price":3639.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9783319911540.webp?v=1769286533","url":"https:\/\/atlanticbooks.com\/products\/analysis-for-computer-scientists-foundations-methods-and-algorithms-9783319911540","provider":"Atlantic Books","version":"1.0","type":"link"}