F# Data
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F# Data | Deedle | |
---|---|---|
6 | 14 | |
805 | 914 | |
0.5% | 0.0% | |
6.8 | 0.0 | |
12 days ago | 10 months ago | |
F# | F# | |
GNU General Public License v3.0 or later | BSD 2-clause "Simplified" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
F# Data
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A new Excel add-in for custom functions and much more using F#. A replacement for VBA?
It is a brilliant tool for being able to import and export data in almost any format from your local computer, a database or across the web. For common data formats like csv, xml, and json, the Type Providers in FSharp.Data allow you automatically generate a type safe API against a sample file.
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Why learn Racket? A student's perspective
F# has this kind of stuff also, where it will dynamically type data dynamic sources like databases or rest calls, etc. for an example https://fsprojects.github.io/FSharp.Data/
- Twenty Years of C# with Anders Hejlsberg [audio]
- FSharp.Data: Data Access Made Simple
- FSharp.Data 4.1.1 Released
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F# Async Webrequest?
Have a look at the FSharp.Data library. It has bunch of cool stuff including Http.
Deedle
What are some alternatives?
TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.
R Provider - Access R packages from F#
Accord.NET
encog-dotnet-core
AForge.NET - AForge.NET Framework is a C# framework designed for developers and researchers in the fields of Computer Vision and Artificial Intelligence - image processing, neural networks, genetic algorithms, machine learning, robotics, etc.
numl - Machine Learning for .NET
Accord.NET Extensions
Infer.NET - UAI 2015. Kernel-based just-in-time learning for expectation propagation
FsLab - FsLab project templates - download as ZIP to get started!