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AI 模型与开发框架教育与学习 high-dimensionalmachine-learningmodelonline-learningparameter-serverscala
6,797
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1,587
Forks
434
Watchers
142
Open Issues
NOASSERTION
许可证
Java
语言
2017-04-25
创建时间
2026-11-12
最近更新

项目能做什么

面向大规模机器学习的高性能、灵活的参数服务器(Parameter Server)。
来源:基于仓库元数据 · 内容以仓库实际 README 为准

使用说明 查看原始 README 原仓库文档

中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
![](assets/angel_logo.png)

[![license](http://img.shields.io/badge/license-Apache2.0-brightgreen.svg?style=flat)](https://github.com/Angel-ML/angel/blob/branch-3.2.0/LICENSE.TXT)
[![Release Version](https://img.shields.io/badge/release-3.2.0-red.svg)](https://github.com/tencent/angel/releases)
[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](https://github.com/tencent/angel/pulls)
[![Download Code](https://img.shields.io/badge/download-zip-green.svg)](https://github.com/Angel-ML/angel/archive/refs/heads/branch-3.2.0.zip)

[(ZH-CN Version)](./README_CN.md)

**Angel** is a high-performance distributed machine learning and graph computing platform based on the philosophy of Parameter Server. It is tuned for performance with big data from Tencent and has a wide range of applicability and stability, demonstrating increasing advantage in handling higher dimension model. Angel is jointly developed by Tencent and Peking University, taking account of both high availability  in industry and innovation in academia.

With model-centered core design concept, **Angel** partitions parameters of complex models into multiple parameter-server nodes, and implements a variety of machine learning algorithms and graph algorithms using efficient model-updating interfaces and functions, as well as flexible consistency model for synchronization.

**Angel** is developed with **Java** and **Scala**.  It supports running on **Yarn**. With **PS Service** abstraction, it supports **Spark on Angel**.  Graph computing and deep learning frameworks support is under development and will be released in the future.

We welcome everyone interested in machine learning or graph computing to contribute code, create issues or pull requests. Please refer to  [Angel Contribution Guide](https://github.com/Tencent/angel/blob/master/CONTRIBUTING.md) for more detail.

## Introduction to Angel

* [Architecture](./docs/overview/architecture_en.md)
* [Code Framework](./docs/overview/code_framework_en.md)
* [Design](./docs/overview/design_philosophy_en.md)
* [Spark on Angel](./docs/overview/spark_on_angel_en.md)
  * [Machine Learning](./docs/overview/spark_on_angel_en.md)
  * [Graph Computing](./docs/overview/angel_graph_sona_en.md)

## Design

- [Model Partitioner](./docs/design/model_partitioner_en.md)
- [SyncController](./docs/design/sync_controller_en.md)
- [psFunc](./docs/design/psfFunc_en.md)
- [Core API](./docs/apis/core_api_en.md)


## Quick Start

* [Quick Start Example](./docs/tutorials/spark_on_angel_quick_start_en.md)

## Deployment

* [Compilation Guide](./docs/deploy/source_compile_en.md)
* [Running on Local](./docs/deploy/local_run_en.md)
* [Running on Yarn](./docs/deploy/run_on_yarn_en.md)
* [Configuration Details](./docs/deploy/config_details_en.md)
* [Resource Configuration Guide](./docs/deploy/resource_config_guide_en.md)

## Programming Guide

* [Spark on Angel Programming Guide](./docs/programmers_guide/spark_on_angel_programing_guide_en.md)

## Algo
阅读完整原文

项目深度分析 规则生成(AI 未配置)

综合评分 55.4 分。该项目在“个人可实施性”维度得 37 分,“付费可能性”维度得 20.0 分,差异化空间 100.0 分(评分依据见评分卡)。

面向细分需求的二次开发产品

产品构想基于 angel 的核心能力,聚焦一个更窄的场景(如某平台、某行业)做差异化。
目标用户该细分场景用户
难度/周期中 · 2~6 周
收费模式买断制 / 订阅制 / 广告
竞争风险细分需求规模需验证
依据 AI 推测:基于项目主题标签的判断
以上为规则引擎基于仓库公开数据生成的参考结论,包含推测成分,不构成投资或创业承诺;配置 AI 后可获得更深入的分析。
报告会保存到 个人中心

竞品与相似项目 GitHub Search 真实检索

相似项目数据正在完善中,暂不展示(避免误导)

项目优势与风险

技术成熟度创建于 2017-04-25,近 30 天仍在推送,发布过 20 个 Release
社区活跃Star 6,797 / Fork 1,587 / Issue 142(数据支持,可自行核实)
许可证NOASSERTION
主要风险上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价

安装与使用

此项目未提供 Docker 镜像,安装步骤以原仓库 README 为准(涉及依赖安装与环境配置,对新手门槛较高)。