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4
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FsLab alternatives and related packages

Based on the "Machine Learning and Data Science" category

  • Accord.NET

    Machine learning framework combined with audio and image processing libraries (computer vision, computer audition, signal processing and statistics).
  • AForge.NET

    Framework for developers and researchers in the fields of Computer Vision and Artificial Intelligence (image processing, neural networks, genetic algorithms, machine learning, robotics).
  • F# Data

    F# type providers for accessing XML, JSON, CSV and HTML files (based on sample documents) and for accessing WorldBank data
  • Accord.NET Extensions

    Advanced image processing and computer vision algorithms made as fluent extensions.
  • encog-dotnet-core

    Encog Machine Learning Framework
  • Deedle

    Data frame and (time) series library for exploratory data manipulation with C# and F# support
  • numl

    5.5 0.0 L3 FsLab VS numl
    Designed to include the most popular supervised and unsupervised learning algorithms while minimizing the friction involved with creating the predictive models.
  • R Provider

    Type provider that exposes R packages and functions in a type-safe way to F# callers
  • Spreads

    Series and Panels for Real-time and Exploratory Analysis of Data Streams. Spreads library is optimized for performance and memory usage. It is several times faster than other open source projects.
  • Infer.NET

    A framework for running Bayesian inference in graphical models. It can also be used for probabilistic programming. [Proprietary] [Free] [Research]

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