distributed
tensorflow/tensorflow347日前180.7k
An Open Source Machine Learning Framework for Everyone
ray-project/ray347日前29.9k
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
ageron/handson-ml347日前25.1k
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
nextcloud/server346日前25.1k
☁️ Nextcloud server, a safe home for all your data
surrealdb/surrealdb346日前24.5k
A scalable, distributed, collaborative, document-graph database, for the realtime web
redisson/redisson345日前22.4k
Redisson - Easy Redis Java client with features of In-Memory Data Grid. Sync/Async/RxJava/Reactive API. Over 50 Redis based Java objects and services: Set, Multimap, SortedSet, Map, List, Queue, Deque, Semaphore, Lock, AtomicLong, Map Reduce, Bloom filter, Spring Cache, Tomcat, Scheduler, JCache API, Hibernate, RPC, local cache ...
phoenixframework/phoenix347日前20.4k
Peace of mind from prototype to production
dgraph-io/dgraph346日前19.9k
The high-performance database for modern applications
dianping/cat346日前18.3k
CAT 作为服务端项目基础组件,提供了 Java, C/C++, Node.js, Python, Go 等多语言客户端,已经在美团点评的基础架构中间件框架(MVC框架,RPC框架,数据库框架,缓存框架等,消息队列,配置系统等)深度集成,为美团点评各业务线提供系统丰富的性能指标、健康状况、实时告警等。
teambit/bit349日前17.4k
A build system for development of composable software.
microsoft/LightGBM346日前15.9k
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.
diaspora/diaspora346日前13.3k
A privacy-aware, distributed, open source social network.
vesoft-inc/nebula346日前9.9k
A distributed, fast open-source graph database featuring horizontal scalability and high availability
orbitdb/orbitdb347日前8.0k
Peer-to-Peer Databases for the Decentralized Web
ipfs/js-ipfs349日前7.5k
IPFS implementation in JavaScript
h2oai/h2o-3346日前6.6k
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.