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Add dathoangnd/gonet (#2905)
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@ -1035,6 +1035,7 @@ See [go-hardware](https://github.com/rakyll/go-hardware) for a comprehensive lis
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* [golinear](https://github.com/danieldk/golinear) - liblinear bindings for Go.
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* [golinear](https://github.com/danieldk/golinear) - liblinear bindings for Go.
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* [GoMind](https://github.com/surenderthakran/gomind) - A simplistic Neural Network Library in Go.
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* [GoMind](https://github.com/surenderthakran/gomind) - A simplistic Neural Network Library in Go.
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* [goml](https://github.com/cdipaolo/goml) - On-line Machine Learning in Go.
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* [goml](https://github.com/cdipaolo/goml) - On-line Machine Learning in Go.
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* [gonet](https://github.com/dathoangnd/gonet) - Neural Network for Go.
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* [Goptuna](https://github.com/c-bata/goptuna) - Bayesian optimization framework for black-box functions written in Go. Everything will be optimized.
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* [Goptuna](https://github.com/c-bata/goptuna) - Bayesian optimization framework for black-box functions written in Go. Everything will be optimized.
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* [goRecommend](https://github.com/timkaye11/goRecommend) - Recommendation Algorithms library written in Go.
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* [goRecommend](https://github.com/timkaye11/goRecommend) - Recommendation Algorithms library written in Go.
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* [gorgonia](https://github.com/gorgonia/gorgonia) - graph-based computational library like Theano for Go that provides primitives for building various machine learning and neural network algorithms.
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* [gorgonia](https://github.com/gorgonia/gorgonia) - graph-based computational library like Theano for Go that provides primitives for building various machine learning and neural network algorithms.
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