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Principles of Data Science: Advanced

In: Data Driven

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  • Jeremy David Curuksu

    (Amazon Web Services, Inc)

Abstract

This chapter covers advanced analytics principles and applications. Let us first back up on our objectives and progress so far. In Chap. 6 , we defined the key concepts underlying the mathematical science of data analysis. The discussion was structured in two categories: descriptive and inferential statistics. In the context of a data science project, these two categories may be referred to as unsupervised and supervised modeling respectively. These two categories are ubiquitous because the objective of a data science project is always (bear with me please) to better understand some data or else to predict something. Chapter 7 thus again follows this binary structure, although some topics (e.g. computer simulation, Sect. 7.3) may be used to collect and understand data, forecast events, or both.

Suggested Citation

  • Jeremy David Curuksu, 2018. "Principles of Data Science: Advanced," Management for Professionals, in: Data Driven, chapter 7, pages 87-127, Springer.
    • Handle: RePEc:spr:mgmchp:978-3-319-70229-2_7
    DOI: 10.1007/978-3-319-70229-2_7
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