COLLOQUIUM ON THE FOUNDATIONS OF MATHEMATICS MATHEMATICAL MACHINES AND THEIR APPLICATIONS PDF Download
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Languages : en
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Author: János Bólyai Mathematical Society
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Languages : en
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Languages : de
Pages : 317
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Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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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 worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
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Languages : en
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Author: Lázló Kalmár
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Category : Calculators
Languages : en
Pages : 330
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Author: L. Kalmar
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Languages : en
Pages : 317
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Languages : de
Pages : 317
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Author: Herb Kunze
Publisher: CRC Press
ISBN: 1000907872
Category : Technology & Engineering
Languages : en
Pages : 530
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Explains the theory behind Machine Learning and highlights how Mathematics can be used in Artificial Intelligence Illustrates how to improve existing algorithms by using advanced mathematics and discusses how Machine Learning can support mathematical modeling Captures how to simulate data by means of artificial neural networks and offers cutting-edge Artificial Intelligence technologies Emphasizes the classification of algorithms, optimization methods, and statistical techniques Explores future integration between Machine Learning and complex mathematical techniques
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Languages : en
Pages : 317
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