MARC details
| 000 -LEADER |
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| fixed length control field |
02128nam a22002417a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20220628121920.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
220628b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9789353164966 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
005.74 |
| Item number |
KAM |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Kamal, Raj |
| 245 ## - TITLE STATEMENT |
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| Title |
Big data analytics: introduction to hadoop, spark, and machine-learning |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc. |
McGraw Hill Education (India) Pvt. Ltd. |
| Place of publication, distribution, etc. |
Chennai |
| Date of publication, distribution, etc. |
2019 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xxvi, 508 p. |
| 365 ## - TRADE PRICE |
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| Price type code |
INR |
| Price amount |
725.00 |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
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.<br/>Highlights:<br/>· 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<br/>· 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.<br/>· Follows a hierarchical and teach-by- example approach from elementary to advanced level.<br/>· Rich pedagogy<br/>· Web supplement includes instructional PPTs, solution of exercises, analysis using open source datasets of a car company, and topics for advanced learning. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Big data |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Electronic data processing |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Strategic planning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Business intelligence |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Information technology |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Saxena, Preeti |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |