Today’s post is a brief example of how to implement a game using F# and SignalR. Creating a game for bots to play doesn’t have to be overly difficult. Since interesting emergent qualities can arise from simple rules, it makes for a fun way to show off SignalR, beyond the standard chat application. As this post will show, F# and SignalR work well together to create a nice communication framework without requiring a complex setup.

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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.

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Today’s post is a introduction to performing json serialization tasks using F# and Chiron.

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Occasionally the need arises in an F# project to perform benchmarking. BenchmarkDotNet is a powerful tool made exactly for this purpose. Today’s post provides an introductory look into the process.

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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.

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