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000938473 019__ $$a1178999610$$a1182862681$$a1183935028
000938473 020__ $$a9783030439811$$q(electronic book)
000938473 020__ $$a303043981X$$q(electronic book)
000938473 020__ $$z3030439801
000938473 020__ $$z9783030439804
000938473 0247_ $$a10.1007/978-3-030-43
000938473 035__ $$aSP(OCoLC)on1176250823
000938473 035__ $$aSP(OCoLC)1176250823$$z(OCoLC)1178999610$$z(OCoLC)1182862681$$z(OCoLC)1183935028
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000938473 049__ $$aISEA
000938473 050_4 $$aQA76.9.B45
000938473 08204 $$a005.7$$223
000938473 24500 $$aPrinciples of data science /$$cHamid R. Arabnia, Kevin Daimi, Robert Stahlbock, Cristina Soviany, Leonard Heilig, Kai Brüssau, editors.
000938473 260__ $$aCham :$$bSpringer,$$c2020.
000938473 300__ $$a1 online resource
000938473 336__ $$atext$$btxt$$2rdacontent
000938473 337__ $$acomputer$$bc$$2rdamedia
000938473 338__ $$aonline resource$$bcr$$2rdacarrier
000938473 4901_ $$aTransactions on computational science and computational intelligence,$$x2569-7072
000938473 500__ $$aIncludes index.
000938473 5050_ $$aIntroduction -- Data Acquisition, Extraction, and Cleaning -- Data Summarization and Modeling -- Data Analysis and Communication Techniques -- Data Science Tools -- Deep Learning in Data Science -- Data Science Applications -- Conclusion.
000938473 506__ $$aAccess limited to authorized users.
000938473 520__ $$aThis book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice.
000938473 650_0 $$aBig data.
000938473 650_0 $$aData mining.
000938473 650_0 $$aStatistics$$xData processing.
000938473 7001_ $$aArabnia, Hamid.
000938473 7001_ $$aDaimi, Kevin.
000938473 7001_ $$aStahlbock, Robert.
000938473 7001_ $$aSoviany, Cristina.
000938473 7001_ $$aHeilig, Leonard.
000938473 7001_ $$aBrüssau, Kai.
000938473 77608 $$iPrint version: $$z3030439801$$z9783030439804$$w(OCoLC)1142035450
000938473 830_0 $$aTransactions on computational science and computational intelligence.
000938473 852__ $$bebk
000938473 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-43981-1$$zOnline Access$$91397441.1
000938473 909CO $$ooai:library.usi.edu:938473$$pGLOBAL_SET
000938473 980__ $$aEBOOK
000938473 980__ $$aBIB
000938473 982__ $$aEbook
000938473 983__ $$aOnline
000938473 994__ $$a92$$bISE