ESSENTIAL MATHEMATICS, EXAMPLES AND EXERCISES

ESSENTIAL MATHEMATICS, EXAMPLES AND EXERCISES

Author: HECTOR NUÑEZ RODRIGUEZ

Publisher: Publisher Venera. Венера

Published: 2016-06-26

Total Pages: 60

ISBN-13:

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This book contains practical exercises and didactic examples, ranging from arithmetic to calculus, including fundamental themes of the algebra and analytic geometry. It is specialized in the teaching and learning of mathematics, in his book and essential levels arises from the problems detected in the knowledge of mathematics at different educational levels. With the skill and judgment of the teacher, the parent or student, this material can be a useful and valuable tool in the rapprochement and gradual mastery of relevant and be mesmerized field of mathematics. With math, everything; nothing without mathematics, it could be the human world he has created and developed the mathematical knowledge as a tool or a key device in the civilizing technological work motto. Mathematical knowledge is also a tool to challenge and intellectual growth, invaluable in the development of the most important brain cognitive abilities


Essential Mathematics for Science and Technology

Essential Mathematics for Science and Technology

Author: K. A. Stroud

Publisher:

Published: 2009

Total Pages: 0

ISBN-13: 9780831133917

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This is an entry level text for a wide range of courses in computer science, medicine, health sciences, social sciences, business, engineering and science. Using the phenomenally successful approach of the bestselling Engineering Mathematics by the same authors, it takes you through the math step-by-step with a wealth of examples and exercises. It is an appropriate refresher or brush-up for sci-tech and business students whose math skills need further development. Offers a unique module approach that takes users through the mathematics in a step-by-step fashion with a wealth of worked examples and exercises. Contains Quizzes, Learning Outcomes and Can You? Checklists that guide readers through each topic and focus understanding. Ideal as reference or a self-learning manual.


Essential Mathematics for Political and Social Research

Essential Mathematics for Political and Social Research

Author: Jeff Gill

Publisher: Cambridge University Press

Published: 2006-04-24

Total Pages: 449

ISBN-13: 0521834260

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"More than ever before, modern social scientists require a basic level of mathematical literacy, yet many students receive only limited mathematical training prior to beginning their research careers. This textbook addresses this dilemma by offering a comprehensive, unified introduction to the essential mathematics of social science. Throughout the book the presentation builds from first principles and eschews unnecessary complexity. Most importantly, the discussion is thoroughly and consistently anchored in real social science applications, with more than 80 research-based illustrations woven into the text and featured in end-of-chapter exercises. Students and researchers alike will find this first-of-its-kind volume to be an invaluable resource."--BOOK JACKET.


Essential Mathematics for Games and Interactive Applications

Essential Mathematics for Games and Interactive Applications

Author: James M. Van Verth

Publisher: CRC Press

Published: 2008-05-19

Total Pages: 706

ISBN-13: 0123742978

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Essential Mathematics for Games and Interactive Applications, 2nd edition presents the core mathematics necessary for sophisticated 3D graphics and interactive physical simulations. The book begins with linear algebra and matrix multiplication and expands on this foundation to cover such topics as color and lighting, interpolation, animation and basic game physics. Essential Mathematics focuses on the issues of 3D game development important to programmers and includes optimization guidance throughout. The new edition Windows code will now use Visual Studio.NET. There will also be DirectX support provided, along with OpenGL - due to its cross-platform nature. Programmers will find more concrete examples included in this edition, as well as additional information on tuning, optimization and robustness. The book has a companion CD-ROM with exercises and a test bank for the academic secondary market, and for main market: code examples built around a shared code base, including a math library covering all the topics presented in the book, a core vector/matrix math engine, and libraries to support basic 3D rendering and interaction.


Essential Mathematics for Undergraduates

Essential Mathematics for Undergraduates

Author: Simon G. Chiossi

Publisher: Springer Nature

Published: 2022-02-16

Total Pages: 495

ISBN-13: 3030871746

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This textbook covers topics of undergraduate mathematics in abstract algebra, geometry, topology and analysis with the purpose of connecting the underpinning key ideas. It guides STEM students towards developing knowledge and skills to enrich their scientific education. In doing so it avoids the common mechanical approach to problem-solving based on the repetitive application of dry formulas. The presentation preserves the mathematical rigour throughout and still stays accessible to undergraduates. The didactical focus is threaded through the assortment of subjects and reflects in the book’s structure. Part 1 introduces the mathematical language and its rules together with the basic building blocks. Part 2 discusses the number systems of common practice, while the backgrounds needed to solve equations and inequalities are developed in Part 3. Part 4 breaks down the traditional, outdated barriers between areas, exploring in particular the interplay between algebra and geometry. Two appendices form Part 5: the Greek etymology of frequent terms and a list of mathematicians mentioned in the book. Abundant examples and exercises are disseminated along the text to boost the learning process and allow for independent work. Students will find invaluable material to shepherd them through the first years of an undergraduate course, or to complement previously learnt subject matters. Teachers may pick’n’mix the contents for planning lecture courses or supplementing their classes.


Algebra: Chapter 0

Algebra: Chapter 0

Author: Paolo Aluffi

Publisher: American Mathematical Soc.

Published: 2021-11-09

Total Pages: 713

ISBN-13: 147046571X

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Algebra: Chapter 0 is a self-contained introduction to the main topics of algebra, suitable for a first sequence on the subject at the beginning graduate or upper undergraduate level. The primary distinguishing feature of the book, compared to standard textbooks in algebra, is the early introduction of categories, used as a unifying theme in the presentation of the main topics. A second feature consists of an emphasis on homological algebra: basic notions on complexes are presented as soon as modules have been introduced, and an extensive last chapter on homological algebra can form the basis for a follow-up introductory course on the subject. Approximately 1,000 exercises both provide adequate practice to consolidate the understanding of the main body of the text and offer the opportunity to explore many other topics, including applications to number theory and algebraic geometry. This will allow instructors to adapt the textbook to their specific choice of topics and provide the independent reader with a richer exposure to algebra. Many exercises include substantial hints, and navigation of the topics is facilitated by an extensive index and by hundreds of cross-references.


Essential Mathematics for Economics and Business

Essential Mathematics for Economics and Business

Author: Teresa Bradley

Publisher: John Wiley & Sons

Published: 2013-05-06

Total Pages: 693

ISBN-13: 1118358295

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Essential Mathematics for Economics and Business is established as one of the leading introductory textbooks on mathematics for students of business and economics. Combining a user–friendly approach to mathematics with practical applications to the subjects, the text provides students with a clear and comprehensible guide to mathematics. The fundamental mathematical concepts are explained in a simple and accessible style, using a wide selection of worked examples, progress exercises and real–world applications. New to this Edition Fully updated text with revised worked examples and updated material on Excel and Powerpoint New exercises in mathematics and its applications to give further clarity and practice opportunities Fully updated online material including animations and a new test bank The fourth edition is supported by a companion website at www.wiley.com/college/bradley, which contains: Animations of selected worked examples providing students with a new way of understanding the problems Access to the Maple T.A. test bank, which features over 500 algorithmic questions Further learning material, applications, exercises and solutions. Problems in context studies, which present the mathematics in a business or economics framework. Updated PowerPoint slides, Excel problems and solutions. "The text is aimed at providing an introductory-level exposition of mathematical methods for economics and business students. In terms of level, pace, complexity of examples and user-friendly style the text is excellent - it genuinely recognises and meets the needs of students with minimal maths background." —Colin Glass, Emeritus Professor, University of Ulster "One of the major strengths of this book is the range of exercises in both drill and applications. Also the 'worked examples' are excellent; they provide examples of the use of mathematics to realistic problems and are easy to follow." —Donal Hurley, formerly of University College Cork "The most comprehensive reader in this topic yet, this book is an essential aid to the avid economist who loathes mathematics!" —Amazon.co.uk


Mathematics for Machine Learning

Mathematics for Machine Learning

Author: Marc Peter Deisenroth

Publisher: Cambridge University Press

Published: 2020-04-23

Total Pages: 392

ISBN-13: 1108569323

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The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.