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003 OCoLC
005 20171025133207.0
006 m o d
007 cr |||||||||||
008 141113s2015 inu ob 001 0 eng d
016 7 _a016976429
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016 7 _a016973753
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020 _a9781118876053
_q(electronic bk.)
020 _a1118876059
_q(electronic bk.)
020 _a1118876229
_q(electronic bk.)
020 _a9781118876220
_q(electronic bk.)
020 _a9781119183686
020 _a1119183685
020 _z9781118876138
020 _z111887613X
024 7 _a10.1002/9781119183686
_2doi
029 1 _aDEBBG
_bBV043398002
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029 1 _aZWZ
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035 _a(OCoLC)898154112
_z(OCoLC)903971073
_z(OCoLC)919280538
_z(OCoLC)926044951
_z(OCoLC)961623598
_z(OCoLC)962624934
037 _aB72C14C8-9461-49F0-AA52-EC8A9FE6E2A7
_bOverDrive, Inc.
_nhttp://www.overdrive.com
040 _aUKMGB
_beng
_epn
_cUKMGB
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049 _aMAIN
050 4 _aQA76.9.D343
072 7 _aCOM
_x000000
_2bisacsh
072 7 _aCOM
_x021030
_2bisacsh
082 0 4 _a006.312
_223
245 0 0 _aData science and big data analytics : discovering, analyzing, visualizing and presenting data /
_cedited by EMC Education Services.
_h[electronic resource]
264 1 _aIndianpolis, IN :
_bJohn Wiley & Sons,
_c2015.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _a1. Introduction to big data analytics -- 2. Data analytics lifecycle -- 3. Review of basic data analytic methods using R -- 4. Advanced analytical theory and methods: clustering -- 5. Advanced analytical theory and methods: association rules -- 6. Advanced analytical theory and methods: regression -- 7. Advanced analytical theory and methods: classification -- 8. Advanced analytical theory and methods: time series analysis -- 9. Advanced analytical theory and methods: text analysis -- 10. Advanced analytics, technology and tools: MapReduce and Hadoop -- 11. Advanced analytics, technology and tools: in-database analytics -- 12. The endgame, or putting it all together.
520 _aThis is a book about harnessing the power of data for new insights and covers the breadth of activities and methods and tools that data scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. It will help you become a contributor on a data science team; deploy a structured lifecycle approach to data analytics problems; apply appropriate analytic techniques and tools to analyzing big data; learn how to tell a compelling story with data to drive business action; prepare for EMC Proven Professional data science certification. --
_cEdited summary from book.
588 0 _aCIP data; item not viewed.
650 0 _aData mining.
650 0 _aBig data.
650 7 _aCOMPUTERS
_xGeneral.
_2bisacsh
650 7 _aCOMPUTERS
_xDatabase Management
_xData Mining.
_2bisacsh
650 7 _aBig data.
_2fast
_0(OCoLC)fst01892965
650 7 _aData mining.
_2fast
_0(OCoLC)fst00887946
655 4 _aElectronic books.
710 2 _aEMC Education Services.
776 0 8 _iPrint version:
_z9781118876138
856 4 0 _uhttp://onlinelibrary.wiley.com/book/10.1002/9781119183686
_zWiley Online Library
942 _2ddc
_cBK
999 _c207800
_d207800