Author: Kirk Weiler
Publisher:
ISBN: 9781944719364
Category :
Languages : en
Pages :
Book Description
N-Gen Math 7: Bundle-20
Author: Kirk Weiler
Publisher:
ISBN: 9781944719364
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781944719364
Category :
Languages : en
Pages :
Book Description
N-Gen Math 7 Bundle - 20
Author: Kirk Weiler
Publisher:
ISBN: 9781944719395
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781944719395
Category :
Languages : en
Pages :
Book Description
N-Gen Math 7
Author: Kirk Weiler
Publisher:
ISBN: 9781944719319
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781944719319
Category :
Languages : en
Pages :
Book Description
N-Gen Math 6: Bundle-20
Author: Kirk Weiler
Publisher:
ISBN: 9781944719623
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781944719623
Category :
Languages : en
Pages :
Book Description
N-Gen Math 8: Bundle - 20
Author: Kirk Weiler
Publisher:
ISBN: 9781944719371
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781944719371
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.
General Mathematics
Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 772
Book Description
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 772
Book Description
Common Core Geometry
Author: Kirk Weiler
Publisher:
ISBN: 9781944719234
Category :
Languages : en
Pages :
Book Description
Publisher:
ISBN: 9781944719234
Category :
Languages : en
Pages :
Book Description
Acing the New SAT Math
Author: Thomas Hyun
Publisher:
ISBN: 9780975475355
Category :
Languages : en
Pages :
Book Description
SAT MATH TEST BOOK
Publisher:
ISBN: 9780975475355
Category :
Languages : en
Pages :
Book Description
SAT MATH TEST BOOK
Introduction to Probability
Author: Joseph K. Blitzstein
Publisher: CRC Press
ISBN: 1466575573
Category : Mathematics
Languages : en
Pages : 599
Book Description
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.
Publisher: CRC Press
ISBN: 1466575573
Category : Mathematics
Languages : en
Pages : 599
Book Description
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.