Mathematics for Machine Learning PDF Download
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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.
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
Get Book Here
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.
Author: Judith A. Beecher
Publisher: Addison-Wesley Longman
ISBN: 9780321693990
Category : Algebra
Languages : en
Pages : 0
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Book Description
Beecher, Penna, and Bittinger's College Algebra is known for enabling students to "see the math" through its focus on visualization and early introduction to functions. With the Fourth Edition, the authors continue to innovate by incorporating more ongoing review to help students develop their understanding and study effectively. Mid-chapter Review exercise sets have been added to give students practice in synthesizing the concepts, and new Study Summaries provide built-in tools to help them prepare for tests. The MyMathLab course (access kit required) has been expanded so that the online content is even more integrated with the text's approach, with the addition of Vocabulary, Synthesis, and Mid-chapter Review exercises from the text as well as example-based videos created by the authors.
Author: Thomas A. Romberg
Publisher: SUNY Press
ISBN: 9780791408995
Category : Mathematics
Languages : en
Pages : 380
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Book Description
Are current testing practices consistent with the goals of the reform movement in school mathematics? If not, what are the alternatives? How can authentic performance in mathematics be assessed? These and similar questions about tests and their uses have forced those advocating change to examine the way in which mathematical performance data is gathered and used in American schools. This book provides recent views on the issues surrounding mathematics tests, such as the need for valid performance data, the implications of the Curriculum and Evaluation Standards for School Mathematics for test development, the identification of valid items and tests in terms of the Standards, the procedures now being used to construct a sample of state assessment tests, gender differences in test taking, and methods of reporting student achievement.
Author: Barbara B.H. Partee
Publisher: Springer Science & Business Media
ISBN: 9789027722454
Category : Language Arts & Disciplines
Languages : en
Pages : 692
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Book Description
Elementary set theory accustoms the students to mathematical abstraction, includes the standard constructions of relations, functions, and orderings, and leads to a discussion of the various orders of infinity. The material on logic covers not only the standard statement logic and first-order predicate logic but includes an introduction to formal systems, axiomatization, and model theory. The section on algebra is presented with an emphasis on lattices as well as Boolean and Heyting algebras. Background for recent research in natural language semantics includes sections on lambda-abstraction and generalized quantifiers. Chapters on automata theory and formal languages contain a discussion of languages between context-free and context-sensitive and form the background for much current work in syntactic theory and computational linguistics. The many exercises not only reinforce basic skills but offer an entry to linguistic applications of mathematical concepts. For upper-level undergraduate students and graduate students in theoretical linguistics, computer-science students with interests in computational linguistics, logic programming and artificial intelligence, mathematicians and logicians with interests in linguistics and the semantics of natural language.
Author: G. Jay Kerns
Publisher: Lulu.com
ISBN: 0557249791
Category : Education
Languages : en
Pages : 388
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Book Description
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Author: Richard Blum
Publisher: John Wiley & Sons
ISBN: 0470554053
Category : Computers
Languages : en
Pages : 384
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Book Description
One of the fastest ways to learn Linux is with this perennial favorite Eight previous top-selling editions of Linux For Dummies can't be wrong. If you've been wanting to migrate to Linux, this book is the best way to get there. Written in easy-to-follow, everyday terms, Linux For Dummies 9th Edition gets you started by concentrating on two distributions of Linux that beginners love: the Ubuntu LiveCD distribution and the gOS Linux distribution, which comes pre-installed on Everex computers. The book also covers the full Fedora distribution. Linux is an open-source operating system and a low-cost or free alternative to Microsoft Windows; of numerous distributions of Linux, this book covers Ubuntu Linux, Fedora Core Linux, and gOS Linux, and includes them on the DVD. Install new open source software via Synaptic or RPM package managers Use free software to browse the Web, listen to music, read e-mail, edit photos, and even run Windows in a virtualized environment Get acquainted with the Linux command line If you want to get a solid foundation in Linux, this popular, accessible book is for you. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Author: Laurence D. Hoffmann
Publisher:
ISBN: 9780071108218
Category : Calculus
Languages : en
Pages :
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Book Description
Calculus for Business, Economics, and the Social and Life Sciences introduces calculus in real-world contexts and provides a sound, intuitive understanding of the basic concepts students need as they pursue careers in business, the life sciences, and the social sciences. The new Ninth Edition builds on the straightforward writing style, practical applications from a variety of disciplines, clear step-by-step problem solving techniques, and comprehensive exercise sets that have been hallmarks of Hoffmann/Bradley's success through the years.
Author: William L. Briggs
Publisher: Addison-Wesley Longman
ISBN: 9780321664150
Category : Calculus
Languages : en
Pages : 0
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Book Description
Drawing on their decades of teaching experience, William Briggs and Lyle Cochran have created a calculus text that carries the teacher's voice beyond the classroom. That voice-evident in the narrative, the figures, and the questions interspersed in the narrative-is a master teacher leading readers to deeper levels of understanding. The authors appeal to readers' geometric intuition to introduce fundamental concepts and lay the foundation for the more rigorous development that follows. Comprehensive exercise sets have received praise for their creativity, quality, and scope. Note: This is the standalone book if you want the book/access card order the ISBN below: 0321665880 / 9780321665881 Multivariable Calculus Plus MyMathLab -- Access Card Package Package consists of: 0321431308 / 9780321431301 MyMathLab/MyStatLab -- Glue-in Access Card 0321654064 / 9780321654069 MyMathLab Inside Star Sticker 0321664159 / 9780321664150 Multivariable Calculus
Author: K. Elayn Martin-Gay
Publisher:
ISBN: 9781256123392
Category : Mathematics
Languages : en
Pages : 0
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Book Description
Author: Christopher M. Bishop
Publisher: Springer
ISBN: 9781493938438
Category : Computers
Languages : en
Pages : 0
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Book Description
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
