FSharp.ML – industry needs. (Machine Learning for .NET)

Machine Learning is a hot topic for nowadays. ML is a core part of Data Analysis and an auxiliary tool in a lot of domains (NLP, search engines, e-commerce solutions and etc). Many ML related courses available on the Coursera  in “Statistics, Data Analysis, and Scientific Computing” and “Computer Science: Artificial Intelligence, Robotics, Vision” sections. Kaggle holds ML competitions more and more often.

Java has some popular and recognized ML libraries such as Mahout and Weka, but it is much harder to find .NET high performance ML library (which does not run on the IKVM.NET).

What is already available in .NET World?

As Don Syme said, it would be cool to have an independent comparison of already available ML libraries. We need to understand what is suitable for what needs.

Also I want to mention some most promising of them:

What can we do?

We are talking that F# is great for data scientists and statisticians and so it is! We still do not have mature F# ML library, but we have a lot of posts about ML and a lot of interest in this domain:

It is time to put it all together into FShapr.ML.  This can be done in two parts: a complete functional ML framework plus a collection of useful customizable samples.

F# Weekly #5, 2013

Welcome to F# Weekly,

A roundup of F# content from this past week:



That’s all for now.  Have a great week.

Previous F# Weekly edition – #4