randomforest
goml
| randomforest | goml | |
|---|---|---|
| 2 | 3 | |
| 46 | 1,551 | |
| - | - | |
| 2.6 | 0.0 | |
| 7 months ago | about 2 years ago | |
| Go | Go | |
| Apache License 2.0 | MIT License |
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randomforest
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Machine Learning
I did end up writing and using a custom library for Random Forest (it's also in AwesomGo) in one real-world project (detecting Alzheimer's and Parkinson's from speech from a mobile app) - https://github.com/malaschitz/randomForest I had better results than the team who used TensorFlow and most importantly I didn't have to use any other technology than Go. For NN's it's probably best to use https://gorgonia.org/ - but it's not exactly a user friendly library. But there is a whole book on it - Hands-On Deep Learning with Go.
- Boruta algorithm added to Random Forest library
goml
- Machine Learning
- GoLang AI/ML open source projects
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I'm looking for a Go computer vision package that isn't GoCV.
I've been meaning to try GoML and Goro, the latter being based on Gorgonia. No idea how relevant either are to your needs.
What are some alternatives?
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
Gorgonia - Gorgonia is a library that helps facilitate machine learning in Go.
sklearn - bits of sklearn ported to Go #golang
gobrain - Neural Networks written in go
EAGO
golinear - liblinear bindings for Go
onnx-go - onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.
go-fann - Go bindings for FANN, library for artificial neural networks
gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
godist - Probability distributions and associated methods in Go