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Mathematics for Machine Learning Paperback - 2020
by Marc Peter Deisenroth; A. Aldo Faisal; Cheng Soon Ong
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- Title Mathematics for Machine Learning
- Author Marc Peter Deisenroth; A. Aldo Faisal; Cheng Soon Ong
- Binding Paperback
- Pages 398
- Volumes 1
- Language ENG
- Publisher Cambridge University Press
- Date 2020-04-23
- ISBN 9781108455145 / 110845514X
- Weight 1.8 lbs (0.82 kg)
- Dimensions 9.84 x 6.93 x 0.87 in (24.99 x 17.60 x 2.21 cm)
- Library of Congress subjects Machine learning - Mathematics
- Library of Congress Catalog Number 2019040762
- Dewey Decimal Code 006.31
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Mathematics for Machine Learning
by Deisenroth, Marc Peter
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Mathematics for Machine Learning
by Marc Peter Deisenroth
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Paperback / softback. 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, optimization, probability and statistics.
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Mathematics for Machine Learning
by Deisenroth, Marc Peter/ Faisal, A. Aldo/ Ong, Cheng Soon
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Cambridge Univ Pr, 2020. Paperback. New. 398 pages. 9.25x6.25x0.25 inches.
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Mathematics for Machine Learning
by Deisenroth, Marc Peter, and Faisal, A Aldo, and Ong, Cheng Soon
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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…
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Mathematics for Machine Learning
by Deisenroth, Marc Peter
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Cambridge University Press, 2020. Soft cover. Very Good. 7x0x10. Book has some intermittent underling and margin marks in pencil on the first 26 pages. Elsewhere, minor wear. ***PROMPT, PROFESSIONAL SERVICE!***
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Mathematics for Machine Learning
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Paperback / softback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; 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 decompositio
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Mathematics for Machine Learning
by Deisenroth, Marc Peter/ Faisal, A. Aldo/ Ong, Cheng Soon
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Cambridge Univ Pr, 2020. Paperback. New. 398 pages. 9.25x6.25x0.25 inches.
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Mathematics for Machine Learning 1st Edition
by Marc Peter Deisenroth
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MATHEMATICS FOR MACHINE LEARNING Paperback – 23 April 2020
by by Marc Peter Deisenroth (Author), & 2 More
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