So I thought to myself, what does the world need? Obviously another brainfuck (BF) compiler. In this series I will use F# and FParsec to compile BF source code into MSIL to run in Microsoft’s CLR. Honestly, this isn’t a particularly ground-breaking task, but it serves as a fun opportunity to showcase a popular parsing library. Beyond that, it shows how easy it is for F# to leverage various parts of the .NET ecosystem.
This post is a follow up to my previous look into Text Analytics. It will provide additional examples of how data can be pulled and processed in F#. I’ll also use this as an opportunity to draw more charts. For all this to happen, I’ll be doing light analysis of the full text of Mary Shelley’s “Frankenstein”.
Today I look into performing linear regression using F#. The implementations of interest will be the MathNet and Accord.NET libraries. I assume you already know what linear regression is, but in can you need a refresher: Linear Regression. My goal is to provide a simple explanation of how to leverage some existing F# accessible libraries. Once you know some of the basic calling functions, you can go crazy with some of the other options these libraries have to offer.
No tech talk today. This is a milestone post. After more hiccups than I’d prefer, the site transition is complete. There has been some minor refactoring with more to follow. Happy prime number new year!