golinear VS goRecommend

Compare golinear vs goRecommend and see what are their differences.

golinear

liblinear bindings for Go (by danieldk)

goRecommend

Collaborative Filtering (CF) Algorithms in Go! (by timkaye11)
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golinear goRecommend
- -
44 203
- -
0.0 0.0
over 5 years ago over 9 years ago
Go Go
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.

golinear

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

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

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.

What are some alternatives?

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

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

go-pr - Pattern recognition package in Go lang.

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

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

GoLearn - Machine Learning for Go

gobrain - Neural Networks written in go

bayesian - Naive Bayesian Classification for Golang.

Varis - Golang Neural Network

go-galib - Genetic Algorithms library written in Go / golang

godist - Probability distributions and associated methods in Go

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