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BIG DATA ANALYTICS, 1ST EDITION
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Overview of BIG DATA ANALYTICS, 1ST EDITION Book
| Title | BIG DATA ANALYTICS, 1ST EDITION |
| Author | Raj Kamal, Preeti Saxena |
| ISBN-13 | 9789353164966 |
| Publication | MHE |
Big Data Analytics (BDA) is a rapidly evolving field that finds applications in many areas such as healthcare, medicine, advertising, marketing, and sales. This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety. It comprises several illustrations, sample codes, case studies and real-life analytics of datasets such as toys, chocolates, cars, and student’s GPAs. The book will serve the interests of undergraduate and post graduate students of computer science and engineering, information technology, and related disciplines. It will also be useful to software developers. Salient Features:• Comprehensive coverage on Big Data NoSQL Column-family, Object and Graph databases, programming with open-source Big Data Hadoop and Spark ecosystem tools, such as MapReduce, Hive, Pig, Spark, Python, Mahout, Streaming, GraphX• Inclusion of latest topics machine learning, K-NN, predictive-analytics, similar and frequent item sets, clustering, decision-tree, classifiers recommenders, real-time streaming data analytics, graph networks, text, web structure, web-links, social network analytics. • Follows a hierarchical and teach-by- example approach from elementary to advanced level.
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Overview of BIG DATA ANALYTICS, 1ST EDITION Book
Big Data Analytics (BDA) is a rapidly evolving field that finds applications in many areas such as healthcare, medicine, advertising, marketing, and sales. This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety. It comprises several illustrations, sample codes, case studies and real-life analytics of datasets such as toys, chocolates, cars, and student’s GPAs. The book will serve the interests of undergraduate and post graduate students of computer science and engineering, information technology, and related disciplines. It will also be useful to software developers. Salient Features:• Comprehensive coverage on Big Data NoSQL Column-family, Object and Graph databases, programming with open-source Big Data Hadoop and Spark ecosystem tools, such as MapReduce, Hive, Pig, Spark, Python, Mahout, Streaming, GraphX• Inclusion of latest topics machine learning, K-NN, predictive-analytics, similar and frequent item sets, clustering, decision-tree, classifiers recommenders, real-time streaming data analytics, graph networks, text, web structure, web-links, social network analytics. • Follows a hierarchical and teach-by- example approach from elementary to advanced level.
Book Type :
Artificial Intelligence
Book Binding :
Not Available
Language :
English
No. of Pages :
542 Pages
ISBN - 10 :
9353164966
ISBN - 13 :
9789353164966
BIG DATA ANALYTICS, 1ST EDITION Published On :
16 February 2019
Publisher :
McGraw Hill Education
Edition :
First Edition
About Raj Kamal, Preeti Saxena:
Raj Kamal, Preeti Saxena is the author of BIG DATA ANALYTICS, 1ST EDITION.
Disclaimer:
- BIG DATA ANALYTICS, 1ST EDITION book is not for reading online or for free download in PDF or eBook format.
- Table of Contents, Index, Syllabus, summary and image of BIG DATA ANALYTICS, 1ST EDITION may be of a different edition or of the same title.
- Price can change due to reprinting, price change by publisher or sourcing cost change for imported books.
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Overview of BIG DATA ANALYTICS, 1ST EDITION Book
| Title | BIG DATA ANALYTICS, 1ST EDITION |
| Author | Raj Kamal, Preeti Saxena |
| ISBN-13 | 9789353164966 |
| Publication | MHE |
Big Data Analytics (BDA) is a rapidly evolving field that finds applications in many areas such as healthcare, medicine, advertising, marketing, and sales. This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety. It comprises several illustrations, sample codes, case studies and real-life analytics of datasets such as toys, chocolates, cars, and student’s GPAs. The book will serve the interests of undergraduate and post graduate students of computer science and engineering, information technology, and related disciplines. It will also be useful to software developers. Salient Features:• Comprehensive coverage on Big Data NoSQL Column-family, Object and Graph databases, programming with open-source Big Data Hadoop and Spark ecosystem tools, such as MapReduce, Hive, Pig, Spark, Python, Mahout, Streaming, GraphX• Inclusion of latest topics machine learning, K-NN, predictive-analytics, similar and frequent item sets, clustering, decision-tree, classifiers recommenders, real-time streaming data analytics, graph networks, text, web structure, web-links, social network analytics. • Follows a hierarchical and teach-by- example approach from elementary to advanced level.