rustmojo

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

The MAX Platform (includes Mojo)

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Inference Llama 2 in one file of pure ?

【重要通知：WebQQ将在2019年1月1日停止服务，此项目目前已停止维护，感谢大家四年来的一路陪伴】使用Perl语言（不会没关系）编写的smartqq/webqq客户端框架（非GUI），可通过插件提供基于HTTP协议的api接口供其他语言或系统调用

使用Perl语言（不会没关系）编写的个人账号微信/weixin/wechat客户端框架（非GUI），可通过插件提供基于HTTP协议的api接口供其他语言或系统调用

Transpiler of Python to many other languages

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.