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”.
F# and Text Analytics
Read Time: 9 minutesToday I look at leveraging F# to perform text analysis using Microsoft’s Cognitive Services.
Linear Regression and F#
Read Time: 8 minutesToday 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.
Site transition complete
Read Time: 1 minutesNo 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!
F# Morse Coder
Read Time: 3 minutesIn other words: -.– .- -.– / ..-. / … …. .- .-. .–.
As I was explaining Morse Code to a young mind, I started thinking. It is fine to explain the encoding and uses, but experiencing the audial component makes the lessons stick better. Enter F#. Yes, I know I could use any of a hundred phone apps or websites that produce sound, but what’s the fun in that? For me, this is the perfect opportunity to hack out a quick text to morse code translator.