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Foster Provost,Tom Fawcett

Data Science for Business

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This broad, deep, but not-too-technical guide introduces you to 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. By learning data science principles, you will understand the many data-mining techniques in use today. More importantly, these principles underpin the processes and strategies necessary to solve business problems through data mining techniques.
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Цитаты

  • Anissa Amandaцитируетв прошлом месяце
    Profiling (also known as behavior description) attempts to characterize the typical behavior of an individual, group, or population. An example profiling question would be: “What is the typical cell phone usage of this customer segment?”
  • Anissa Amandaцитируетв прошлом месяце
    Co-occurrence grouping (also known as frequent itemset mining, association rule discovery, and market-basket analysis) attempts to find associations between entities based on transactions involving them
  • Anissa Amandaцитируетв прошлом месяце
    Clustering attempts to group individuals in a population together by their similarity

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