The art and practice of data science pipelines: A comprehensive study of data science pipelines in theory, in-the-small, and in-the-large
Increasingly larger number of software systems today are including data science
components for descriptive, predictive, and prescriptive analytics. The collection of data
science stages from acquisition, to cleaning/curation, to modeling, and so on are referred to
as data science pipelines. To facilitate research and practice on data science pipelines, it is
essential to understand their nature. What are the typical stages of a data science pipeline?
How are they connected? Do the pipelines differ in the theoretical representations and that …
components for descriptive, predictive, and prescriptive analytics. The collection of data
science stages from acquisition, to cleaning/curation, to modeling, and so on are referred to
as data science pipelines. To facilitate research and practice on data science pipelines, it is
essential to understand their nature. What are the typical stages of a data science pipeline?
How are they connected? Do the pipelines differ in the theoretical representations and that …
[PDF][PDF] The art and practice of data science pipelines
Increasingly larger number of software systems today are including data science
components for descriptive, predictive, and prescriptive analytics. The collection of data
science stages from acquisition, to cleaning/curation, to modeling, and so on are referred to
as data science pipelines. To facilitate research and practice on data science pipelines, it is
essential to understand their nature. What are the typical stages of a data science pipeline?
How are they connected? Do the pipelines differ in the theoretical representations and that …
components for descriptive, predictive, and prescriptive analytics. The collection of data
science stages from acquisition, to cleaning/curation, to modeling, and so on are referred to
as data science pipelines. To facilitate research and practice on data science pipelines, it is
essential to understand their nature. What are the typical stages of a data science pipeline?
How are they connected? Do the pipelines differ in the theoretical representations and that …
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