Invitation to Discrete Mathematics PDF Download

Author: Jiří Matoušek
Publisher: Oxford University Press
ISBN: 0198570430
Category : Mathematics
Languages : en
Pages : 462

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Book Description
A clear and self-contained introduction to discrete mathematics for undergraduates and early graduates.

Author: Canada. Legislature. Legislative Assembly
Publisher:
ISBN:
Category :
Languages : en
Pages : 656

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Book Description

Author: Ivor Grattan-Guinness
Publisher: Birkhäuser
ISBN: 3034878117
Category : Mathematics
Languages : en
Pages : 1580

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Book Description

Author: Lou Lecacheur
Publisher:
ISBN: 9782218741821
Category :
Languages : fr
Pages : 58

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Book Description

Author: N. Bourbaki
Publisher: Springer Science & Business Media
ISBN: 9783540642435
Category : Mathematics
Languages : en
Pages : 750

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Book Description
An exposition of the fundamentals of general, linear and multilinear algebra. The first chapter introduces the basic objects: groups, actions, rings, fields. The second chapter studies the properties of modules and linear maps, and the third investigatesalgebras, particularly tensor algebras.

Author: André Mul
Publisher:
ISBN: 9782218741838
Category :
Languages : fr
Pages : 58

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Book Description

Author: Nicolas Bourbaki
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 432

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Book Description

Author: N. Bourbaki
Publisher: Springer Science & Business Media
ISBN: 3642593151
Category : Mathematics
Languages : en
Pages : 343

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Book Description
This is an English translation of Bourbaki’s Fonctions d'une Variable Réelle. Coverage includes: functions allowed to take values in topological vector spaces, asymptotic expansions are treated on a filtered set equipped with a comparison scale, theorems on the dependence on parameters of differential equations are directly applicable to the study of flows of vector fields on differential manifolds, etc.

Author: Nancy D. Anderson
Publisher: American Mathematical Soc.
ISBN: 9780821801291
Category : Mathematics
Languages : en
Pages : 198

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Book Description
Intended for mathematics librarians, the list allows librarians to ascertain if a seminaire has been published, which library has it, and the forms of entry under which it has been cataloged.

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.