Language:
English
Pages:
1 online resource (1 volume)
,
illustrations
Edition:
First edition.
Keywords:
F♯ (Computer program language)
;
Machine learning
;
Electronic books
;
Electronic books ; local
Abstract:
In this report, F# contributor Tomas Petricek explains many of the key features of the F# language that make it a great tool for data science and machine learning. Real world examples take you through the entire data science workflow with F#, from data access and analysis to presenting the results. You'll learn about: How F# and its unique features-such as type providers-ease the chore of data access The process of data analysis and visualization, using the Deedle library, R type provider and the XPlot charting library Implementations for a clustering algorithm using the standard F# library and how the F# type inference helps you understand your code The report also includes a list of resources to help you learn more about using F# for data science.
Note:
Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed January 8, 2019)
URL:
https://learning.oreilly.com/library/view/-/9781492048350/?ar
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