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goptuna: hyperparameter optimization framework. (#2636)

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Masashi SHIBATA 2019-08-09 22:53:02 +09:00 committed by Bo-Yi Wu
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@ -971,6 +971,7 @@ See [go-hardware](https://github.com/rakyll/go-hardware) for a comprehensive lis
* [golinear](https://github.com/danieldk/golinear) - liblinear bindings for Go. * [golinear](https://github.com/danieldk/golinear) - liblinear bindings for Go.
* [GoMind](https://github.com/surenderthakran/gomind) - A simplistic Neural Network Library in Go. * [GoMind](https://github.com/surenderthakran/gomind) - A simplistic Neural Network Library in Go.
* [goml](https://github.com/cdipaolo/goml) - On-line Machine Learning in Go. * [goml](https://github.com/cdipaolo/goml) - On-line Machine Learning in Go.
* [Goptuna](https://github.com/c-bata/goptuna) - Bayesian optimization framework for black-box functions written in Go. Everything will be optimized.
* [goRecommend](https://github.com/timkaye11/goRecommend) - Recommendation Algorithms library written in Go. * [goRecommend](https://github.com/timkaye11/goRecommend) - Recommendation Algorithms library written in Go.
* [gorgonia](https://github.com/chewxy/gorgonia) - graph-based computational library like Theano for Go that provides primitives for building various machine learning and neural network algorithms. * [gorgonia](https://github.com/chewxy/gorgonia) - graph-based computational library like Theano for Go that provides primitives for building various machine learning and neural network algorithms.
* [gorse](https://github.com/zhenghaoz/gorse) - A High Performance Recommender System Package based on Collaborative Filtering for Go. * [gorse](https://github.com/zhenghaoz/gorse) - A High Performance Recommender System Package based on Collaborative Filtering for Go.