F# Data alternatives and similar packages
Based on the "Machine Learning and Data Science" category.
Alternatively, view F# Data alternatives based on common mentions on social networks and blogs.
ML.NET9.6 7.0 F# Data VS ML.NETML.NET is an open source and cross-platform machine learning framework for .NET.
Accord.NET9.5 6.7 L2 F# Data VS Accord.NETMachine learning framework combined with audio and image processing libraries (computer vision, computer audition, signal processing and statistics).
TensorFlow.NET8.3 1.3 F# Data VS TensorFlow.NET.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.
AForge.NET7.1 0.0 L2 F# Data VS AForge.NETAForge.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.
Deedle6.3 2.7 F# Data VS DeedleEasy to use .NET library for data and time series manipulation and for scientific programming
Accord.NET Extensions6.1 0.0 L5 F# Data VS Accord.NET ExtensionsAdvanced image processing and computer vision algorithms made as fluent extensions.
encog-dotnet-core5.5 0.0 F# Data VS encog-dotnet-coreEncog Machine Learning Framework
numl5.3 0.0 L3 F# Data VS numlMachine Learning for .NET
Catalyst5.0 5.6 F# Data VS Catalyst🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
Spreads4.6 3.5 F# Data VS SpreadsSeries and Panels for Real-time and Exploratory Analysis of Data Streams
R Provider4.3 0.0 F# Data VS R ProviderAccess R packages from F#
Synapses2.3 0.0 F# Data VS SynapsesA group of neural-network libraries for functional and mainstream languages
Infer.NET1.8 0.0 F# Data VS Infer.NETUAI 2015. Kernel-based just-in-time learning for expectation propagation
FsLab1.4 0.0 F# Data VS FsLabFsLab project templates - download as ZIP to get started!
SciSharp STACKA rich machine learning ecosystem for .NET created by porting the most popular Python libraries to C#.
Access the most powerful time series database as a service
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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FSharp.Data: Making Data Access Simple
The FSharp.Data package (
FSharp.Data.dll) implements everything you need to access data in your F# applications and scripts. It implements F# type providers for working with structured file formats (CSV, HTML, JSON and XML) and for accessing the WorldBank data. It also includes helpers for parsing CSV, HTML and JSON files and for sending HTTP requests.
We're open to contributions from anyone. If you want to help out but don't know where to start, you can take one of the Up-For-Grabs issues, or help to improve the documentation.
You can see the version history [here](RELEASE_NOTES.md).
- Install the .NET SDK specified in the
build.sh -t Buildor
build.cmd -t Build
dotnet fake build -t Format dotnet fake build -t CheckFormat
This library comes with comprehensive documentation. The documentation is
automatically generated from
*.fsx files in the content folder and from the comments in the code. If you find a typo, please submit a pull request!
- FSharp.Data package home page with more information about the library, contributions, etc.
- The samples from the documentation are included as part of
FSharp.Data.Tests.sln, make sure you build the solution before trying out the samples to ensure that all needed packages are installed.
Releasing of the NuGet package is done by GitHub actions CI from master branch when a new version is pushed.
Releasing of docs is done by GitHub actions CI on each push to master branch.
Support and community
- If you have a question about
FSharp.Data, ask at StackOverflow and mark your question with the
- If you want to submit a bug, a feature request or help with fixing bugs then look at issues and read contributing to FSharp.Data.
- To discuss more general issues about FSharp.Data, its goals and other open-source F# projects, join the fsharp-opensource mailing list
Code of Conduct
This repository is governed by the Contributor Covenant Code of Conduct.
We pledge to be overt in our openness, welcoming all people to contribute, and pledging in return to value them as whole human beings and to foster an atmosphere of kindness, cooperation, and understanding.
The library is available under Apache 2.0. For more information see the License file in the GitHub repository.
Current maintainers are Don Syme and Phillip Carter
Historical maintainers of this project are Gustavo Guerra, Tomas Petricek and Colin Bull.
*Note that all licence references and agreements mentioned in the F# Data README section above are relevant to that project's source code only.