Data Mining for Business & Governance

Tilburg University (UVT)

Here are the best resources to pass Data Mining for Business & Governance. Find Data Mining for Business & Governance study guides, notes, assignments, and much more.

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Alle lectures content Data Mining for Businnes & Governance
  • Alle lectures content Data Mining for Businnes & Governance

  • Class notes • 51 pages • 2024
  • Document containing all the information for the Data Mining for Business & Governance course. This course is given in spring 2024.
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Data Mining for Business & Governance (880662-M-6)
  • Data Mining for Business & Governance (880662-M-6)

  • Summary • 60 pages • 2023
  • Grade: 9.0. Extensive summary for the course Data Mining for Business and Governance. The summary contains the content of all lectures and tutorials (the theory, not the coding), including additional notes, examples and explanations. I also incorporated parts of the relevant chapters of the following books (in the form of supplementing the lecture content): (1) Data mining: concepts and techniques (3rd edition) by Jiawei Han, Micheline Kamber, Jian Pei (H-Book), (2) Data Mining: The Textbook by ...
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Summary Data Mining for Business & Governance
  • Summary Data Mining for Business & Governance

  • Summary • 65 pages • 2021
  • Summary Data Mining for Business & Governance, written in the spring semester of 2021 for Data Science & Society, Tilburg University.
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Samenvatting Data Mining for buisiness and governance
  • Samenvatting Data Mining for buisiness and governance

  • Summary • 69 pages • 2021
  • Een gedetailleerde samenvatting over het vak data mining van alle collegeslides en aantekeningen inclusief voorbeelden van de algorithmes.
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Data Mining for Business And Governance
  • Data Mining for Business And Governance

  • Summary • 47 pages • 2021
  • Summary of full course
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Summary Data Mining | Midterm week 1-3
  • Summary Data Mining | Midterm week 1-3

  • Summary • 30 pages • 2020
  • This summary includes all material of week 1-3. It serves for the first midterm of this course. * Lectures notes: 1-3
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