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Add "ocrserver" (#2436)
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@ -921,6 +921,7 @@ See [go-hardware](https://github.com/rakyll/go-hardware) for a comprehensive lis
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* [mlgo](https://github.com/NullHypothesis/mlgo) - This project aims to provide minimalistic machine learning algorithms in Go.
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* [mlgo](https://github.com/NullHypothesis/mlgo) - This project aims to provide minimalistic machine learning algorithms in Go.
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* [neat](https://github.com/jinyeom/neat) - Plug-and-play, parallel Go framework for NeuroEvolution of Augmenting Topologies (NEAT).
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* [neat](https://github.com/jinyeom/neat) - Plug-and-play, parallel Go framework for NeuroEvolution of Augmenting Topologies (NEAT).
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* [neural-go](https://github.com/schuyler/neural-go) - Multilayer perceptron network implemented in Go, with training via backpropagation.
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* [neural-go](https://github.com/schuyler/neural-go) - Multilayer perceptron network implemented in Go, with training via backpropagation.
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* [ocrserver](https://github.com/otiai10/ocrserver) - A simple OCR API server, seriously easy to be deployed by Docker and Heroku.
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* [probab](https://github.com/ThePaw/probab) - Probability distribution functions. Bayesian inference. Written in pure Go.
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* [probab](https://github.com/ThePaw/probab) - Probability distribution functions. Bayesian inference. Written in pure Go.
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* [regommend](https://github.com/muesli/regommend) - Recommendation & collaborative filtering engine.
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* [regommend](https://github.com/muesli/regommend) - Recommendation & collaborative filtering engine.
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* [shield](https://github.com/eaigner/shield) - Bayesian text classifier with flexible tokenizers and storage backends for Go.
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* [shield](https://github.com/eaigner/shield) - Bayesian text classifier with flexible tokenizers and storage backends for Go.
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