An Open Source Machine Learning Framework for Everyone

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A cloud-native vector database, storage for next generation AI applications

A scalable, distributed, collaborative, document-graph database, for the realtime web

A distributed task scheduling framework.（分布式任务调度平台XXL-JOB）

☁️ Nextcloud server, a safe home for all your data

🤖 The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

High-performance, scalable time-series database designed for Industrial IoT (IIoT) scenarios

Redisson - Valkey and Redis Java client. Complete Real-Time Data Platform. Sync/Async/RxJava/Reactive API. Over 50 Valkey and Redis based Java objects and services: Set, Multimap, SortedSet, Map, List, Queue, Deque, Semaphore, Lock, AtomicLong, Map Reduce, Bloom filter, Spring, Tomcat, Scheduler, JCache API, Hibernate, RPC, local cache..

Peace of mind from prototype to production

The database for modern applications. Common use cases: knowledge graphs for AI, fraud detection, personalization, and search. Built and maintained by @hypermodeinc.

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。

A build system for development of composable software.

Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

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.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

A privacy-aware, distributed, open source social network.

A hyperparameter optimization framework

A distributed, fast open-source graph database featuring horizontal scalability and high availability