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    Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking (Paperback) By (author) Foster Provost, By (author) Tom Fawcett

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    DescriptionWritten by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You'll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company's data science projects. You'll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization - and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you're to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

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    Data Science for Business
    What You Need to Know About Data Mining and Data-Analytic Thinking
    Authors and contributors
    By (author) Foster Provost, By (author) Tom Fawcett
    Physical properties
    Format: Paperback
    Number of pages: 408
    Width: 178 mm
    Height: 231 mm
    Thickness: 25 mm
    Weight: 680 g
    ISBN 13: 9781449361327
    ISBN 10: 1449361323

    BIC E4L: COM
    B&T Book Type: NF
    B&T Modifier: Region of Publication: 01
    B&T Modifier: Subject Development: 10
    Nielsen BookScan Product Class 3: S10.3T
    Warengruppen-Systematik des deutschen Buchhandels: 16320
    DC22: 006.312
    B&T Modifier: Academic Level: 03
    B&T Modifier: Text Format: 06
    B&T General Subject: 229
    B&T Modifier: Text Format: 01
    B&T Merchandise Category: COM
    BISAC V2.8: BUS061000
    BIC subject category V2: KJMV3
    BISAC V2.8: BUS091000
    LC subject heading: , ,
    Ingram Subject Code: XD
    LC subject heading:
    B&T Approval Code: A93662400
    LC subject heading:
    BISAC V2.8: COM021030
    B&T Approval Code: A93700000
    BISAC V2.8: COM062000
    DC22: 006.3/12
    BIC subject category V2: UNF
    DC23: 658.40380285574
    LC subject heading: ,
    LC classification: QA76.9.D343 P77 2013
    Thema V1.0: KCH, KJQ, KJMK, UNF
    Illustrations note
    illustrations (black and white), charts
    O'Reilly Media, Inc, USA
    Imprint name
    O'Reilly Media, Inc, USA
    Publication date
    01 September 2013
    Publication City/Country
    Author Information
    Foster Provost is a Professor and NEC Faculty Fellow at the NYU Stern School of Business, where he has taught data science to MBAs for 15 years. His research and teaching focus on data science, machine learning, business analytics, (social) network data, and crowd-sourcing for data analytics. Tom Fawcett has a Ph.D. in machine learning from UMass-Amherst and has worked in industrial research (GTE Laboratories, NYNEX/Verizon Labs, HP Labs, etc.). He has served as action editor of the Machine Learning journal, before which he was an editorial board member.