Analyzing and visualizing data with F♯ - Petricek, Tomas (O'Reilly Media, 2015)
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.