goRecommend VS bayesian

Compare goRecommend vs bayesian and see what are their differences.

goRecommend

Collaborative Filtering (CF) Algorithms in Go! (by timkaye11)

bayesian

Naive Bayesian Classification for Golang. (by jbrukh)
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goRecommend bayesian
- -
203 784
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0.0 2.3
over 9 years ago 5 months ago
Go Go
MIT License GNU General Public License v3.0 or later
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.

goRecommend

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

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

bayesian

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

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

What are some alternatives?

When comparing goRecommend and bayesian you can also consider the following projects:

go-pr - Pattern recognition package in Go lang.

Gorgonia - Gorgonia is a library that helps facilitate machine learning in Go.

neural-go - A multilayer perceptron network implemented in Go, with training via backpropagation.

GoLearn - Machine Learning for Go

gobrain - Neural Networks written in go

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

Varis - Golang Neural Network

godist - Probability distributions and associated methods in Go

gosseract - Go package for OCR (Optical Character Recognition), by using Tesseract C++ library

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

goga - Golang Genetic Algorithm