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Nikolay 2020-12-26 12:01:06 +08:00
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@ -416,8 +416,8 @@ Read the paper [here](https://arxiv.org/abs/1902.06714).
* [leaves](https://github.com/dmitryikh/leaves) - A pure Go implementation of the prediction part of GBRTs, including XGBoost and LightGBM.
* [gobrain](https://github.com/goml/gobrain) - Neural Networks written in Go.
* [go-featureprocessing](https://github.com/nikolaydubina/go-featureprocessing) - Fast and convenient feature processing for low latency machine learning in Go.
* [go-ml-transpiler](https://github.com/znly/go-ml-transpiler) - An open source Go transpiler for machine learning models.
* [go-mxnet-predictor](https://github.com/songtianyi/go-mxnet-predictor) - Go binding for MXNet c_predict_api to do inference with a pre-trained model.
* [go-ml-transpiler](https://github.com/znly/go-ml-transpiler) - An open source Go transpiler for machine learning models.
* [golearn](https://github.com/sjwhitworth/golearn) - Machine learning for Go.
* [goml](https://github.com/cdipaolo/goml) - Machine learning library written in pure Go.
* [gorgonia](https://github.com/gorgonia/gorgonia) - Deep learning in Go.