Today we’ll look at performing sentiment analysis using F# and ML.NET. A new version (v0.9.0) has recently been released, so we use this as an opportunity to play with some new functionality. The goal of today’s post will be to perform sentiment analysis on movie reviews from IMDB.
With the release of v0.7.0, it is time to revisit K-means clustering using F# and Microsoft’s new ML.NET framework. The api has changed enough to warrant a minor rework. This post is a re-examination of a previous post F# and ML.NET Clustering. The use case will be to use examination attributes to classify mammogram results.
Recently I was working on a project using F# and Elasticsearch. I thought it would be fun to post a light introduction. Nicely enough, Elastic provides a .NET client, two actually here. They are a combination of low level and high level interfaces. As is sometimes the case, using F# and C#-style libraries requires some clever navigation of the interface. For this post I will only focus on the high level interface (NEST).