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.
Table of Contents
- 1. Accessing Data with Type Providers
- 2. Analyzing Data Using F# and Deedle
- 3. Implementing Machine Learning Algorithms
- 4. Conclusions and Next Steps
- Title: Analyzing and Visualizing Data with F#
- Release date: October 2015
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781492048350