000 02722cam a2200385 i 4500
001 23228178
003 US-DLC
005 20251102105619.0
008 230714s2024 nyu b 001 0 eng
010 _a 2023024328
020 _a9780231206860
_q(hardback)
020 _z9780231556699
_q(ebook)
035 _a23228178
040 _aau
_beng
_erda
_cDLC
_dau
042 _apcc
049 _aAlfaisal Main Library
050 0 0 _aHD30.215
_b.F74 2024
100 1 _aFreidman, Howard Steven,
_eauthor.
245 1 0 _aWinning with data science :
_ba handbook for business leaders /
_cHoward Steven Freidman and Akshay Swaminathan.
260 _c2024
264 1 _aNew York :
_bColumbia Business School Publishing,
_c[2024]
300 _ax, 259 pages ;
_c23 cm
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 _aTools of the Trade -- The Data Science Project -- Data Science Foundations -- Making Decisions with Data -- Clustering, Segmenting, and Cutting Through the Noise -- Building Your First Model -- Tools for Machine Learning -- Pulling It Together -- Ethics.
520 _a"Data science is increasingly important in the business world, not just for the teams in charge of implementing it but the professionals adjacent to them. Yet not all businesspeople have a general understanding of the basics-and if senior management assigns them to work alongside a data science team, they'll need that knowledge as soon as possible without having to take online courses or dive down the Internet rabbit hole. This book provides that knowledge base, walking readers through the key ideas needed to communicate and work with a data science team. They will be able to understand the basic technical lingo, recognize the types of talent on the team and pose good questions to your data scientists to open up more insights, create opportunities, and generate value. By the end of the book they will be able to answer key questions including how data is collected and stored, what hardware and software tools are needed to analyze data, who does what on the data science team and which models should be considered for specific projects. Most critically, they will also be armed with critical questions that you can use to further probe data analysts, statisticians, data scientists and other technical experts to better understand the value of their work for a business"--
650 0 _aManagement
_xStatistical methods.
650 0 _aDatabases.
650 0 _aData mining.
650 0 _aElectronic data processing.
655 0 _aPrint books.
_2local
_94
942 _2lcc
_cBOOKS
999 _c607766
_d607766