Edité par Cambridge University Press, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 47,71
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Edité par Cambridge University Press, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 53,06
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Goodbooks Company, Springdale, AR, Etats-Unis
EUR 55,10
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : good. Has a sturdy binding with some shelf wear. May have some markings or highlighting. Used copies may not include access codes or Cd's. Slight bending may be present.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Books From California, Simi Valley, CA, Etats-Unis
EUR 60,04
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierhardcover. Etat : Very Good.
Edité par Cambridge University Press, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 48,81
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierEtat : New.
Edité par Cambridge University Press, GB, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : Rarewaves USA, OSWEGO, IL, Etats-Unis
EUR 70
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierPaperback. Etat : New. 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.
Edité par Cambridge University Press, GB, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
EUR 71
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierPaperback. Etat : New. 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.
Edité par Cambridge University Press, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 56,62
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierEtat : As New. Unread book in perfect condition.
EUR 49,70
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierPaperback. Etat : Brand New. 398 pages. 9.25x6.25x0.25 inches. In Stock.
Edité par Cambridge University Press, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : moluna, Greven, Allemagne
EUR 46,85
Autre deviseQuantité disponible : 3 disponible(s)
Ajouter au panierEtat : New. This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, .
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 98,59
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
EUR 97,42
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 101,03
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
EUR 77,76
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierPaperback. Etat : Brand New. 398 pages. 9.25x6.25x0.25 inches. In Stock.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : California Books, Miami, FL, Etats-Unis
EUR 109,74
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Ajouter au panierEtat : New.
Edité par Cambridge University Press, GB, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : Rarewaves USA United, OSWEGO, IL, Etats-Unis
EUR 72
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierPaperback. Etat : New. 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.
Edité par Cambridge University Press CUP, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Books Puddle, New York, NY, Etats-Unis
EUR 114,39
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : New.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 104,63
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. In.
Edité par Cambridge University Press 2020-04-23, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Chiron Media, Wallingford, Royaume-Uni
EUR 102,37
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierHardcover. Etat : New.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 104,61
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Majestic Books, Hounslow, Royaume-Uni
EUR 116,71
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : New.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
EUR 119,50
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Cambridge University Press, GB, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Rarewaves USA, OSWEGO, IL, Etats-Unis
EUR 138,38
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierHardback. Etat : New. 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.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
EUR 124,06
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierEtat : New.
Edité par Cambridge University Press, GB, 2020
ISBN 10 : 110845514X ISBN 13 : 9781108455145
Langue: anglais
Vendeur : Rarewaves.com UK, London, Royaume-Uni
EUR 65,76
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierPaperback. Etat : New. 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.
Edité par Cambridge University Press, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
EUR 125,83
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : New. New. book.
Edité par Cambridge University Press, GB, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
EUR 162,10
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierHardback. Etat : New. 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.
Edité par Cambridge University Press, 2021
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : moluna, Greven, Allemagne
EUR 112,87
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierGebunden. Etat : New. This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, .
EUR 148,55
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierHardcover. Etat : Brand New. 398 pages. 10.00x7.00x1.00 inches. In Stock.
Edité par Cambridge University Press, GB, 2020
ISBN 10 : 1108470041 ISBN 13 : 9781108470049
Langue: anglais
Vendeur : Rarewaves USA United, OSWEGO, IL, Etats-Unis
EUR 140,88
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierHardback. Etat : New. 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.