Data Science for Business - E-book - Multi-format

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Tom Fawcett - Data Science for Business.
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science,... Lire la suite
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Résumé

Written 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

Caractéristiques

  • Date de parution
    27/07/2013
  • Editeur
    O'Reilly Media
  • ISBN
    978-1-4493-6131-0
  • EAN
    9781449361310
  • Format
    Multi-format
  • Nb. de pages
    408 pages
  • Caractéristiques du format Multi-format
    • Pages
      408
  • Caractéristiques du format ePub
    • Protection num.
      pas de protection
  • Caractéristiques du format PDF
    • Protection num.
      pas de protection
  • Caractéristiques du format Mobipocket
    • Protection num.
      pas de protection
  • Caractéristiques du format Streaming
    • Protection num.
      pas de protection

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À propos de l'auteur

Biographie de Tom Fawcett

Tom Fawcett holds a Ph. D. in machine learning and has worked in industry R&D for more than two decades (GTE Laboratories, NYNEX/Verizon Labs, HP Labs, etc.). His published work has become standard reading in data science both on methodology (e.g., evaluating data mining results) and on applications (e.g., fraud detection and spam filtering). Foster Provost is Professor and NEC Faculty Fellow at the NYU Stern School of Business where he teaches in the MBA, Business Analytics, and Data Science programs.
His award-winning research is read and cited broadly. Prof. Provost has co-founded several successful companies focusing on data science for marketing.

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