m2cgen VS Infer.NET

Compare m2cgen vs Infer.NET and see what are their differences.

m2cgen

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies (by BayesWitnesses)

Infer.NET

UAI 2015. Kernel-based just-in-time learning for expectation propagation (by wittawatj)
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m2cgen Infer.NET
8 -
2,706 17
0.5% -
0.0 0.0
6 months ago about 5 years ago
Python MATLAB
MIT License 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.

m2cgen

Posts with mentions or reviews of m2cgen. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-02.

Infer.NET

Posts with mentions or reviews of Infer.NET. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Infer.NET yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing m2cgen and Infer.NET you can also consider the following projects:

Accord.NET

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

Synapses - A group of neural-network libraries for functional and mainstream languages

R Provider - Access R packages from F#

gorse - Gorse open source recommender system engine

randomforest - Random Forest implementation in golang

gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)

ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.

sklearn - bits of sklearn ported to Go #golang

go-fann - Go bindings for FANN, library for artificial neural networks

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.

FsLab - FsLab project templates - download as ZIP to get started!