Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Goodwill of Greater Milwaukee and Chicago, Racine, WI, Estados Unidos de America
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
EUR 39,19
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Añadir al carritoCondición: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Marlton Books, Bridgeton, NJ, Estados Unidos de America
EUR 38,77
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Añadir al carritoCondición: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. paperback Used - Acceptable 2020.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Chapter Two Bookstore, Lompoc, CA, Estados Unidos de America
EUR 37,22
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Añadir al carritoSoft cover. Condición: Very Good. Book and cover look really nice. Binding is tight and square. Book is clean as a whistle inside and out with minor shelf wear.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: WeBuyBooks, Rossendale, LANCS, Reino Unido
EUR 31,68
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Añadir al carritoCondición: Very Good. Most items will be dispatched the same or the next working day. A copy that has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 49,93
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 54,70
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Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Textbooks_Source, Columbia, MO, Estados Unidos de America
Original o primera edición
EUR 51,40
Cantidad disponible: 17 disponibles
Añadir al carritopaperback. Condición: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Idioma: Inglés
Publicado por Cambridge University Press 4/23/2020, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 55,82
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Añadir al carritoPaperback or Softback. Condición: New. Mathematics for Machine Learning. Book.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 56,51
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Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 53,24
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
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Idioma: Inglés
Publicado por Cambridge University Pr., 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: CollegePoint, Inc, Jamestown, TN, Estados Unidos de America
Original o primera edición
EUR 53,18
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Añadir al carritoPaperback. Condición: Good. 1st Edition. We only honor returns for quality issues and won't accept reasons such as 'change my mind', 'find a better price', or 'school book requirement change', etc.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 59,38
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Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Speedyhen LLC, Hialeah, FL, Estados Unidos de America
EUR 62,28
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Idioma: Inglés
Publicado por Cambridge University Press, Cambridge, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Original o primera edición
EUR 62,92
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. Paperback. 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. 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, optimization, probability and statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Publicado por Cambridge University Press, GB, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 64,93
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPaperback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, GB, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
EUR 66,33
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPaperback. Condición: 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.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: GoldBooks, Denver, CO, Estados Unidos de America
EUR 62,39
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. New Copy. Customer Service Guaranteed.
Idioma: Inglés
Publicado por Cambridge University Press CUP, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 64,72
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: MostlyAcademic, Berrima, NSW, Australia
Original o primera edición
EUR 38,15
Cantidad disponible: 1 disponibles
Añadir al carritoSoft cover. Condición: Fine. 1st Edition.
Idioma: Inglés
Publicado por Cambridge University Press 2020-04-23, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Chiron Media, Wallingford, Reino Unido
EUR 50,85
Cantidad disponible: 10 disponibles
Añadir al carritoPaperback. Condición: New.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 51,61
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Majestic Books, Hounslow, Reino Unido
EUR 61,94
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 56,92
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Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 61,04
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Añadir al carritoCondición: New.
Idioma: Inglés
Publicado por Cambridge University Pr. Apr 2020, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 49,80
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Neuware -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. 371 pp. Englisch.
Idioma: Inglés
Publicado por Cambridge University Pr. Apr 2020, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Alemania
EUR 49,80
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Neuware -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. 371 pp. Englisch.
Idioma: Inglés
Publicado por Cambridge University Press, 2020
ISBN 10: 110845514X ISBN 13: 9781108455145
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 64,05
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. 2020. Paperback. . . . . .