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Analyzing and visualizing data with F♯ /

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....

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Petricek, Tomas (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, [2015]
Edición:First edition.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 |a 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. 
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