waveletai


Namewaveletai JSON
Version 0.2.38 PyPI version JSON
download
home_pagehttps://ai.xiaobodata.com/
SummaryWaveletAI A Machine Learning Lifecycle Platform
upload_time2023-01-16 08:32:23
maintainer
docs_urlNone
authorJanus
requires_python>=3.6
license
keywords ml ai waveletai
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # [WaveletAI](market.xiaobodata.com) <img src="http://oss.xiaobodata.com/public/product/logo/wai.png" width="45" />
<a href="http://gitlab.xiaobodata.com/FirstGroup/WAI/waveletai/-/commits/master"><img alt="pipeline status" src="http://gitlab.xiaobodata.com/FirstGroup/WAI/waveletai/badges/master/pipeline.svg" /></a>
<a href="http://gitlab.xiaobodata.com/FirstGroup/WAI/waveletai/-/commits/master"><img alt="coverage report" src="http://gitlab.xiaobodata.com/FirstGroup/WAI/waveletai/badges/master/coverage.svg" /></a>

A Machine Learning Lifecycle Platform for AI/ML individuals and teams. 



小波AI是一个集合数据、编程、模型、算力、服务的一站式协同开发云平台,提供全栈的AI能力。

在这里,你可以根据业务需要,轻松的来训练、部署、管理和跟踪你的模型。

小波AI已在服务于微企多个团队,稳定运行了一年,大大加速了AI项目的实施和推进速度,目前在平台已经完成了上百种模型的前期验证、训练和发布,并在AI市场中发布了多种能力。



> Power By [WaveletPlus](http://plus.xiaobodata.com/) <img src="http://oss.xiaobodata.com/public/product/logo/wavelet_plus.png" width="45" />

## 功能特性

### 全生命周期跟踪

- 小波AI会自动关联跟踪记录模型运行时信息,记录训练过程状态和运行数据,支持自定义参数、指标设置并生成实时日志,帮助你快速进行试验,验证想法;

- 小波AI支持完全支持用于跟踪工作的 Git 存储库(支持HTTP/SSH双协议),在向小波AI提交模型训练时,系统会将有关存储库的信息作为训练过程的一部分进行跟踪;


### 丰富的AI套件支持

小波AI平台可用于任何类型的机器学习,从传统 ml 到深度学习、监督式和非监督式学习。无论你是否希望编写 Python 或 R 代码,你都可以在小波AI中构建、训练和跟踪你的模型。

该平台还可与常用的AI套件快速集成(如 PyTorch、TensorFlow 、keras、xgboost、 scikit-learn、lightgbm、spark、onnx等)。


### 为大型项目协作而生

- 小波AI适用于大型项目开发场景,让你从大量的离线作业中脱身出来,不同角色得人都可以在平台中实现快速协作;

- 用DevOps的方式管理你的ML工作,从开发到部署的自动流程化实现。大大降低模型迭代开发及部署实施的难度;

- 提供强有力的设备算力支持和资源分配策略,让你可以在CPU、GPU设备上快速训练;

- 通用权限设计,满足组内成果共享和组间权限控制等实际场景,让多项目并行管理不再困难;

- 无需调整业务应用接口,支持模型版本的在线更新;

### 在任何地方以相同方式运行

- 小波AI 会将项目模型打包为再任何平台上可重现的模式;

- 一键发布模型,快速实现模型的云端和终端设备部署;


## 团队

@Author  : WaveletAI-Product-Team

            

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