000			02532nam a22002057a 4500
999			_c21472 _d21472
020			_a9789353164973
041			_aENG
082			_a005.74 _bKAM
100			_aKamal, Raj
245			_aBig data analytics : _bintroduction to hadoop, spark, and machine-learning / _cRaj Kamal and Preeti Saxena
260			_aChennai : _bMcGraw Hill Education, _cc2019
300			_axxvi, 508 pages : _billustrations; _c25 cm.
505			_a1. Introduction to Big Data Analytics 2. Introduction to Hadoop 3. NoSQL Big Data Management, MongoDB and Cassandra 4. MapReduce, Hive and Pig 5. Spark and Big Data Analytics 6. Machine Learning Algorithms for Big Data Analytics 7. Data Stream Mining and Real-Time Analytics Platform—SparkStreaming 8. Graph Analytics for Big Data and Spark GraphX Platform 9. Text, Web Content, Link, and Social Network Analytics 10. Programming Examples in Analytics and Machine Learning using Hadoop, Spark and Python
520			_aBig 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. Highlights: · 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. · Rich pedagogy · Web supplement includes instructional PPTs, solution of exercises, analysis using open source datasets of a car company, and topics for advanced learning.
650			_aElectronic data processing
650			_aBusiness intelligence
650			_aInformation technology
700			_aSaxena, Preeti
942			_2ddc _cBK