GoLearn
Gorgonia
| GoLearn | Gorgonia | |
|---|---|---|
| 3 | 22 | |
| 9,304 | 5,578 | |
| - | 0.7% | |
| 0.0 | 1.1 | |
| 11 months ago | 4 months ago | |
| Go | Go | |
| MIT License | Apache License 2.0 |
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.
GoLearn
- Machine Learning
- GoLang AI/ML open source projects
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Multi-layer neural network from scratch in Go
If you're curious about a more robust machine learning library in Go, https://github.com/sjwhitworth/golearn is a quite feature-rich option.
Gorgonia
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ML in Go with a Python Sidecar
For Go specifically, there are some libraries like Gorgonia (https://github.com/gorgonia/gorgonia) that can do inference.
Practically speaking though, the rate at which models change is so fast that if you opt to go this route, you'll perpetually be lagging behind the state of the art by just a bit. Either you'll be the one implementing the latest improvements or be waiting for the framework to catch up. This is the real value of the sidecar approach: when a new technique comes out (like speculative decoding, for example) you don't need to reimplement it in Go but instead can use the implementation that most other python users will use.
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Machine Learning en GO! 🤯
GitHub - gorgonia/gorgonia: Gorgonia is a library that helps facilitate machine learning in Go.
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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.
- Why isn’t Go used in AI/ML?
- GoLang AI/ML open source projects
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A systematic framework for technical documentation authoring
Perhaps it's a product of French culture, but because Gorgonia[0] has a number of French contributors, this was actually the way we structured our documentation.
But this is the first time I've heard of the name of the framework.
[0]: https://gorgonia.org
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[D] When was the last time you wrote a custom neural net?
Oh it's.Gorgonia
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Most Popular GoLang Frameworks
Website: https://gorgonia.org
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[D] What framework are you using?
I use Gorgonia.
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Why can't Go be popular for machine learning?
What you think about this https://github.com/gorgonia/gorgonia ? I also recall there is something else out there but can't find it at the moment...
What are some alternatives?
sklearn - bits of sklearn ported to Go #golang
onnx-go - onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.
goml - On-line Machine Learning in Go (and so much more)
tfgo - Tensorflow + Go, the gopher way
neural-go - A multilayer perceptron network implemented in Go, with training via backpropagation.
gosseract - Go package for OCR (Optical Character Recognition), by using Tesseract C++ library
randomforest - Random Forest implementation in golang
bayesian - Naive Bayesian Classification for Golang.
regommend - Recommendation engine for Go
go-deep - Artificial Neural Network