F# Data VS ML.NET

Compare F# Data vs ML.NET and see what are their differences.

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F# Data ML.NET
6 17
805 8,846
0.6% 0.5%
6.8 8.9
14 days ago 3 days ago
F# C#
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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

Posts with mentions or reviews of F# Data. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-21.

ML.NET

Posts with mentions or reviews of ML.NET. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-25.

What are some alternatives?

When comparing F# Data and ML.NET you can also consider the following projects:

Deedle - Easy to use .NET library for data and time series manipulation and for scientific programming

TensorFlow.NET - .NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.

Accord.NET

R Provider - Access R packages from F#

FaceRecognitionDotNet - The world's simplest facial recognition api for .NET on Windows, MacOS and Linux

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.

OpenCvSharp - OpenCV wrapper for .NET

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.

numl - Machine Learning for .NET