Author: Barnard SMITH
Publisher:
ISBN:
Category :
Languages : en
Pages : 76
Book Description
Exercises in Arithmetic. pt. 1
Exercises in Analysis
Author: Leszek Gasi Ski
Publisher:
ISBN: 9783319061771
Category :
Languages : en
Pages : 1048
Book Description
Publisher:
ISBN: 9783319061771
Category :
Languages : en
Pages : 1048
Book Description
John Heywood's Manchester readers. [With] Key, pt.1,2. Primer
Mathematics for Machine Learning
Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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.
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392
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.
Rudiments of Mathematics Part 1
Author:
Publisher: Academic Publishers
ISBN: 9788189781545
Category :
Languages : en
Pages : 956
Book Description
Publisher: Academic Publishers
ISBN: 9788189781545
Category :
Languages : en
Pages : 956
Book Description
Mathematics Action P4b Pt1 Wb
Author: Swee Fong Ng
Publisher: Pearson Education South Asia
ISBN: 9789812443205
Category : Mathematics
Languages : en
Pages : 108
Book Description
Publisher: Pearson Education South Asia
ISBN: 9789812443205
Category : Mathematics
Languages : en
Pages : 108
Book Description
Mathematics Action P3b Pt1 Wb
Author:
Publisher: Pearson Education South Asia
ISBN: 9789814110280
Category :
Languages : en
Pages : 84
Book Description
Publisher: Pearson Education South Asia
ISBN: 9789814110280
Category :
Languages : en
Pages : 84
Book Description
The American Educational Catalogue
A Latin Vocabulary; Arranged on Etymological Principles, as an Exercise-book and First Latin Dictionary
Author: Benjamin Hall Kennedy
Publisher:
ISBN:
Category :
Languages : en
Pages : 146
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 146
Book Description