go-deep VS goRecommend

Compare go-deep vs goRecommend and see what are their differences.

Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
go-deep goRecommend
- -
510 203
- -
3.5 0.0
3 months ago over 9 years ago
Go 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.

go-deep

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

We haven't tracked posts mentioning go-deep 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 go-deep and goRecommend you can also consider the following projects:

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

go-pr - Pattern recognition package in Go lang.

tfgo - Tensorflow + Go, the gopher way

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

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

gobrain - Neural Networks written in go

shield - Bayesian text classifier with flexible tokenizers and storage backends for Go

Varis - Golang Neural Network

godist - Probability distributions and associated methods in Go

GoLearn - Machine Learning for 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