Author: Larson
Publisher:
ISBN: 9781680330557
Category :
Languages : en
Pages :
Book Description
Big Ideas Math Integrated Mathematics I Resources by Chapter
Author: Larson
Publisher:
ISBN: 9781680330557
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781680330557
Category :
Languages : en
Pages :
Book Description
Big Ideas Math Integrated I
Author: Houghton Mifflin Harcourt
Publisher:
ISBN: 9781680331127
Category : Algebra
Languages : en
Pages : 784
Book Description
Publisher:
ISBN: 9781680331127
Category : Algebra
Languages : en
Pages : 784
Book Description
Big Ideas Math Integrated Mathematics III
Author: Houghton Mifflin Harcourt
Publisher:
ISBN: 9781680330878
Category : Algebra
Languages : en
Pages : 688
Book Description
Publisher:
ISBN: 9781680330878
Category : Algebra
Languages : en
Pages : 688
Book Description
Big Ideas Math Integrated Mathematics II
Author: Houghton Mifflin Harcourt
Publisher:
ISBN: 9781680330687
Category : Algebra
Languages : en
Pages : 832
Book Description
Publisher:
ISBN: 9781680330687
Category : Algebra
Languages : en
Pages : 832
Book Description
Big Ideas Math Integrated Mathematics I Teaching Edition
Author: Larson
Publisher:
ISBN: 9781680330519
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781680330519
Category :
Languages : en
Pages :
Book Description
Integrated Math, Course 1, Student Edition
Author: CARTER 12
Publisher: McGraw-Hill Education
ISBN: 9780076638581
Category : Mathematics
Languages : en
Pages : 1152
Book Description
Includes: Print Student Edition
Publisher: McGraw-Hill Education
ISBN: 9780076638581
Category : Mathematics
Languages : en
Pages : 1152
Book Description
Includes: Print Student Edition
Big Ideas Math Integrated Mathematics III Resources by Chapter
Author: Larson
Publisher:
ISBN: 9781680330939
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781680330939
Category :
Languages : en
Pages :
Book Description
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.
Integrated Math, Course 2, Student Edition
Author: CARTER 12
Publisher: McGraw-Hill Education
ISBN: 9780076638611
Category : Mathematics
Languages : en
Pages : 1056
Book Description
Includes: Print Student Edition
Publisher: McGraw-Hill Education
ISBN: 9780076638611
Category : Mathematics
Languages : en
Pages : 1056
Book Description
Includes: Print Student Edition
Big Ideas Math Integrated Mathematics I Assessment Book
Author: Larson
Publisher:
ISBN: 9781680330540
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781680330540
Category :
Languages : en
Pages :
Book Description