Author: Theodore Shifrin
Publisher: Macmillan
ISBN: 1429215216
Category : Mathematics
Languages : en
Pages : 394
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Book Description
Linear Algebra: A Geometric Approach, Second Edition, presents the standard computational aspects of linear algebra and includes a variety of intriguing interesting applications that would be interesting to motivate science and engineering students, as well as help mathematics students make the transition to more abstract advanced courses. The text guides students on how to think about mathematical concepts and write rigorous mathematical arguments.
Author: Joel Robbin
Publisher:
ISBN:
Category :
Languages : en
Pages : 133
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Book Description
This is an extensive textbook and study manual for University Level First Semester Calculus (Math 221). The Book has concepts, problems and solutions for the topic.
Author: Sigurd Angenent
Publisher:
ISBN: 9781505204841
Category :
Languages : en
Pages : 134
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Book Description
MATH 221 FIRST Semester CalculusBy Sigurd Angenent
Author: László Lovász
Publisher: Springer Science & Business Media
ISBN: 0387217770
Category : Mathematics
Languages : en
Pages : 344
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Book Description
Aimed at undergraduate mathematics and computer science students, this book is an excellent introduction to a lot of problems of discrete mathematics. It discusses a number of selected results and methods, mostly from areas of combinatorics and graph theory, and it uses proofs and problem solving to help students understand the solutions to problems. Numerous examples, figures, and exercises are spread throughout the book.
Author: University of Michigan
Publisher:
ISBN:
Category : Detroit (Mich.)
Languages : en
Pages : 1680
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Book Description
Announcements for the following year included in some vols.
Author: James W. Demmel
Publisher: SIAM
ISBN: 0898713897
Category : Mathematics
Languages : en
Pages : 426
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Book Description
This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines.
Author: James Stewart
Publisher: Brooks Cole
ISBN: 9780534251581
Category : Mathematics
Languages : en
Pages : 1148
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Book Description
In this version of his best-selling text, Stewart has reorganized the material so professors can teach transcendental functions (more than just trigonometric functions) early, before the definite integral. This variation introduces the derivative of the log and exponential functions at the same time as the polynomial functions and develops other transcendental functions prior to the introduction of the definite integral..In the new Third Edition, Stewart retains the focus on problem solving, the meticulous accuracy, the patient explanations, and the carefully graded problems that have made this text work so well for a wide range of students. In the new edition, Stewart has increased his emphasis on technology and innovation and has expanded his focus on problem-solving and applications. ..When writing his previous editions, Stewart set out to bring some of the spirit of Polya to his presentation. This resulted in the ''strategy sections'' in the First Edition and the ''Problems Plus'' and ''Applications Plus'' sections in the Second Edition. Now in the Third Edition, he extends the idea further with a new section on ''Principles of Problem Solving'' and new extended examples in the ''Problems Plus'' and ''Applications Plus'' sections. Stewart makes a serious attempt to help students reason mathematically.
Author: Georgia B. Pyrros
Publisher:
ISBN: 9780787244279
Category : Mathematics
Languages : en
Pages : 216
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Book Description
Author: James Stewart
Publisher: Thomson Brooks/Cole
ISBN: 9780495012399
Category : Mathematics
Languages : en
Pages : 0
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Book Description
This helpful guide contains a short list of key concepts; a short list of skills to master; a brief introduction to the ideas of the section; an elaboration of the concepts and skills, including extra worked-out examples; and links in the margin to earlier and later material in the text and Study Guide.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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Book Description
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.
