m2cgen VS godist

Compare m2cgen vs godist 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)

godist

Probability distributions and associated methods in Go (by e-dard)
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m2cgen godist
8 -
2,706 36
0.6% -
0.0 0.0
6 months ago almost 9 years ago
Python Go
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.

godist

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

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

What are some alternatives?

When comparing m2cgen and godist you can also consider the following projects:

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

goRecommend - Collaborative Filtering (CF) Algorithms in Go!

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

goga - Golang Genetic Algorithm

R Provider - Access R packages from F#

goml - On-line Machine Learning in Go (and so much more)

gorse - Gorse open source recommender system engine

neat

randomforest - Random Forest implementation in golang

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

GoLearn - Machine Learning for Go