Articles liés à Probability and Statistics for Data Science

Probability and Statistics for Data Science - Couverture souple

Livre 1 sur 36: Chapman & Hall/CRC Data Science

Matloff, Norman

 
9781138393295: Probability and Statistics for Data Science
Couverture souple
ISBN 10 : 1138393290 ISBN 13 : 9781138393295
Editeur : Routledge, 2019

Synopsis

Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously:

* Real datasets are used extensively.

* All data analysis is supported by R coding.

* Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks.

* Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture."

* Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner.

Prerequisites are calculus, some matrix algebra, and some experience in programming.

Norman Matloff

 is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics

in 2017. He is a recipient of his university's Distinguished Teaching Award.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Routledge
Date d'édition
2019
Langue
anglais
ISBN 10 
1138393290
ISBN 13 
9781138393295
Reliure
Broché
Nombre de pages
412
Coordonnées du fabricant
non disponible
Personne responsable
non disponible