10

8

6

4

2


9.7

9.4

9.6

5.9

7.1
0.0

6.4

5.1

6.3

6.8

15 Machine Learning and Data Science packages and projects

  • ML.NET

    9.7 9.4 C#
    Cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
  • Accord.NET

    9.6 5.9 L2 C#
    Machine learning framework combined with audio and image processing libraries (computer vision, computer audition, signal processing and statistics).
  • AForge.NET

    7.1 0.0 L2 C#
    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

    6.4 5.1 HTML
    F# type providers for accessing XML, JSON, CSV and HTML files (based on sample documents) and for accessing WorldBank data
  • Deedle

    6.3 6.8 F#
    Data frame and (time) series library for exploratory data manipulation with C# and F# support
  • Accord.NET Extensions

    6.1 0.0 L5 C#
    Advanced image processing and computer vision algorithms made as fluent extensions.
  • encog-dotnet-core

    5.7 0.0 C#
    Encog Machine Learning Framework
  • numl

    5.5 0.4 L3 C#
    Designed to include the most popular supervised and unsupervised learning algorithms while minimizing the friction involved with creating the predictive models.
  • Spreads

    4.1 8.9 C#
    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.
  • R Provider

    3.9 3.0 F#
    Type provider that exposes R packages and functions in a type-safe way to F# callers
  • Catalyst

    3.2 8.5 C#
    Catalyst Cross-platform Natural Language Processing (NLP) library inspired by spaCy, with pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models. Part of the SciSharp Stack
  • Infer.NET

    1.9 0.0 Matlab
    A framework for running Bayesian inference in graphical models. It can also be used for probabilistic programming. [Proprietary] [Free] [Research]
  • Synapses

    1.6 7.8 F#
    An in-memory neural network library written in F#.
  • FsLab

    1.4 0.0
    A collection of data science and machine learning libraries for F# and .NET
  • SciSharp STACK

    - -
    A rich machine learning ecosystem for .NET created by porting the most popular Python libraries to C#.

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