Librería: SpringBooks, Berlin, Alemania
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Idioma: Inglés
Publicado por Springer Nature Singapore, Springer Nature Singapore, 2017
ISBN 10: 9811068070 ISBN 13: 9789811068072
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 90,34
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book helps readers understand the mathematics of machine learning, and apply them in different situations. It is divided into two basic parts, the first of which introduces readers to the theory of linear algebra, probability, and data distributions and it's applications to machine learning. It also includes a detailed introduction to the concepts and constraints of machine learning and what is involved in designing a learning algorithm. This part helps readers understand the mathematical and statistical aspects of machine learning.In turn, the second part discusses the algorithms used in supervised and unsupervised learning. It works out each learning algorithm mathematically and encodes it in R to produce customized learning applications. In the process, it touches upon the specifics of each algorithm and the science behind its formulation.The book includes a wealth of worked-out examples along with R codes. It explains the code for each algorithm, and readerscan modify the code to suit their own needs. The book will be of interest to all researchers who intend to use R for machine learning, and those who are interested in the practical aspects of implementing learning algorithms for data analysis. Further, it will be particularly useful and informative for anyone who has struggled to relate the concepts of mathematics and statistics to machine learning.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 70,24
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer Nature Singapore Dez 2017, 2017
ISBN 10: 9811068070 ISBN 13: 9789811068072
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 85,59
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book helps readers understand the mathematics of machine learning, and apply them in different situations. It is divided into two basic parts, the first of which introduces readers to the theory of linear algebra, probability, and data distributions and it's applications to machine learning. It also includes a detailed introduction to the concepts and constraints of machine learning and what is involved in designing a learning algorithm. This part helps readers understand the mathematical and statistical aspects of machine learning.In turn, the second part discusses the algorithms used in supervised and unsupervised learning. It works out each learning algorithm mathematically and encodes it in R to produce customized learning applications. In the process, it touches upon the specifics of each algorithm and the science behind its formulation.The book includes a wealth of worked-out examples along with R codes. It explains the code for each algorithm, and readers can modify the code to suit their own needs. The book will be of interest to all researchers who intend to use R for machine learning, and those who are interested in the practical aspects of implementing learning algorithms for data analysis. Further, it will be particularly useful and informative for anyone who has struggled to relate the concepts of mathematics and statistics to machine learning. 232 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 72,89
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Abhijit Ghatak is a Data Scientist and holds an ME in Engineering and MS in Data Science from Stevens Institute of Technology, USA. He started his career as a submarine engineer officer in the Indian Navy and worked on multiple data-intensive projects in.
Idioma: Inglés
Publicado por Springer, Springer Dez 2017, 2017
ISBN 10: 9811068070 ISBN 13: 9789811068072
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 85,59
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿Help readers understand the mathematical interpretation of learning algorithmsSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 232 pp. Englisch.