000			01377nam a22001697a 4500
999			_c655951 _d655951
008			200219b ||||| |||| 00| 0 eng d
020			_a9789352133741
082			_a006.312/BEN/KIM
100			_aBENGFORT, BENJAMIN
245			_aDATA ANALYTICS WITH HADOOP: AN INTRODUCTION FOR DATA SCIENTISTS
260			_aNavi Mumbai _bShroff Publishers and Distributors Pvt. Ltd _c2019
300			_axvi, 268p
520			_aThis book ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operationsor software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop providesand higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hiveand HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data.
650			_aDATA MINING, FILE ORGANIZATION (COMPUTER SCIENCE), APACHE HADOOP
700			_aKIM, JENNY
942			_2ddc _cB