### F# is Part of Microsoft's Data Science Workloads

I have not worked in F# for over two (2) years, but am enthused that Microsoft has added it to it languages for Data Science Workloads, along with R and Python. To that end, I hope to repost some of my existing F# code, as well as explore Data Science Workloads utilizing all three languages. Prior work in F# is available from learning F#, and some solutions will be republished on this site.

### Data Science Workloads

### Published Work in F#

- James Igoe MS Azure Notebooks that utilizes MS's implementation of Jupyter Notesbooks.
- Mathematical Library, a basic mathematical NuGet package, with the source hosted on GitHub.
- Basic Statistical Functions: Very basic F# class for performing standard deviation and variance calculations.
- Various Number Functions: A collection of basic mathematical functions written in F# as part of my learning via Project Euler, functions for creating arrays or calculating values in various data structures.

### Explored in F#

I explored F# some time ago, intrigued by the idiom of functional languages and the strengths of F#. Additionally, some solutions can improved upon by using .NET components to speed the process, e.g., parallel processing, and the language itself is not simply functional, but can also be used for object-oriented and procedural development.- Functions (non-state, no side effects)
- Tail recursion
- Non-mutable variables
- Currying
- Lambda notation
- Pattern matching
- Sequences, arrays, lists, and tuples
- Array slicing