Microsoft to Boost F# Machine Learning Functionality
In announcing an update to its open source F# functional programming language, Microsoft indicated future releases will better support machine learning projects.
Specifically, the company said, F# will work better with the open source TensorFlow machine learning library.
"Finally, we're also devoting significant time in developing a compelling offering for using F# to do machine learning. In addition to being supported on ML.NET, we're working towards a world-class experience when using F# and TensorFlow," Microsoft said in describing future work in a post about the new F# 4.6 update.
That world-class experience will start with the TensorFlow.FSharp GitHub project, described as a work in progress that features two components:
- TensorFlow.FSharp: An F# API for TensorFlow
- FM: A prototype of a DSL "F# for AI Models". This currently executes using TensorFlow.FSharp but could have additional backends such as DiffSharp.
"TensorFlow shape checking and shape inference tie quite nicely into the F# type system and tools, which we feel is a differentiator when compared to using Python, Swift or Scala," the March 29 post continued. "This is still an active research area, but over time we expect the experience to become quite solid as F# Interactive experiences on .NET Core also shape up."
F# Interactive (fsi.exe) is used to run F# code interactively at the console, or to execute F# scripts.
As far as F# 4.6, Microsoft said the primary focus of the update is to boost performance, especially for medium-to-large sized solutions. Part of that work involved removing a workaround to a previous IntelliSense bug that actually "resulted in horrible performance characteristics."
David Ramel is the editor of Visual Studio Magazine.