Machine Learning Models and Algorithms for Big Data Classification: Thinking With Examples for Effective Learning

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9781489976406: Machine Learning Models and Algorithms for Big Data Classification: Thinking With Examples for Effective Learning
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Shan Suthaharan
Edité par Springer-Verlag New York Inc., United States (2015)
ISBN 10 : 148997640X ISBN 13 : 9781489976406
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Description du livre Springer-Verlag New York Inc., United States, 2015. Hardback. État : New. 2016 ed.. 235 x 155 mm. Language: English . Brand New Book. This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems.The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems. N° de réf. du libraire LIB9781489976406

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SHAN SUTHAHARAN
Edité par Springer (2015)
ISBN 10 : 148997640X ISBN 13 : 9781489976406
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Herb Tandree Philosophy Books
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Description du livre Springer, 2015. Hardback. État : NEW. 9781489976406 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. N° de réf. du libraire HTANDREE0956004

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Shan Suthaharan
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ISBN 10 : 148997640X ISBN 13 : 9781489976406
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Description du livre Springer 2015-12-15, 2015. Hardcover. État : New. N° de réf. du libraire NU-LBR-01703110

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Shan Suthaharan
Edité par Springer-Verlag New York Inc., United States (2015)
ISBN 10 : 148997640X ISBN 13 : 9781489976406
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Description du livre Springer-Verlag New York Inc., United States, 2015. Hardback. État : New. 2016 ed.. 235 x 155 mm. Language: English . Brand New Book. This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems.The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems. N° de réf. du libraire LIB9781489976406

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Shan Suthaharan
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Description du livre Springer-Verlag New York Inc., 2015. HRD. État : New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N° de réf. du libraire IP-9781489976406

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Suthaharan, Shan
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Description du livre Springer, 2016. Paperback. État : New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. N° de réf. du libraire ria9781489976406_lsuk

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Shan Suthaharan
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Description du livre Springer-Verlag New York Inc., 2015. HRD. État : New. New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000. N° de réf. du libraire IP-9781489976406

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Shan Suthaharan
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Description du livre Springer-Verlag New York Inc. 2015-10-21, New York, 2015. hardback. État : New. N° de réf. du libraire 9781489976406

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Shan Suthaharan
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Description du livre Springer, 2015. État : New. N° de réf. du libraire L9781489976406

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Shan Suthaharan
Edité par Springer-Verlag Gmbh Nov 2015 (2015)
ISBN 10 : 148997640X ISBN 13 : 9781489976406
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Description du livre Springer-Verlag Gmbh Nov 2015, 2015. Buch. État : Neu. 247x167x27 mm. Neuware - This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. 355 pp. Englisch. N° de réf. du libraire 9781489976406

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