ML.NET: ML.NET 是一个跨平台的开源机器学习框架,旨在让 .NET 开发者更快上手机器学习

代码拉取完成,页面将自动刷新

扫描微信二维码支付

取消

支付完成

richgiteeai

Watch

不关注关注所有动态仅关注版本发行动态关注但不提醒动态

1 Star 0 Fork 9

aaronwang/ML.NET

forked from Gitee 极速下载/ML.NET

代码 Wiki 统计流水线

服务

加入 Gitee

与超过 1400万开发者一起发现、参与优秀开源项目,私有仓库也完全免费 :)

免费加入

已有帐号? 立即登录

克隆/下载

HTTPS SSH SVN SVN+SSH 下载ZIP

提示

下载代码请复制以下命令到终端执行

为确保你提交的代码身份被 Gitee 正确识别,请执行以下命令完成配置

git config --global user.name userName 
git config --global user.email userEmail

初次使用 SSH 协议进行代码克隆、推送等操作时,需按下述提示完成 SSH 配置

1 生成 RSA 密钥

2 获取 RSA 公钥内容,并配置到 SSH公钥中

在 Gitee 上使用 SVN,请访问使用指南

使用 HTTPS 协议时,命令行会出现如下账号密码验证步骤。基于安全考虑,Gitee 建议配置并使用私人令牌替代登录密码进行克隆、推送等操作

Username for 'https://gitee.com': userName

Password for 'https://userName@gitee.com': # 私人令牌

新建文件

新建子模块

上传文件

分支 147

标签 70

贡献代码

同步代码

创建 Pull Request

了解更多

对比差异通过 Pull Request 同步

同步更新到分支

通过 Pull Request 同步

将会在向当前分支创建一个 Pull
Request,合入后将完成同步

Xiaoyun Zhang update max_model when trial fails (#6596) cb7b724

2685 次提交

.github

build

docs

eng

src

test

tools-local

.editorconfig

.gitattributes

.gitignore

.gitmodules

.vsts-dotnet-ci.yml

CODE_OF_CONDUCT.md

CONTRIBUTING.md

Directory.Build.props

Directory.Build.targets

ISSUE_TEMPLATE.md

LICENSE

Microsoft.ML.sln

NuGet.config

PULL_REQUEST_TEMPLATE.md

README-oneDAL.md

README.ko-KR.md

README.md

ROADMAP.md

SECURITY.md

THIRD-PARTY-NOTICES.TXT

build.cmd

build.sh

codecov.yml

dir.traversal.targets

global.json

restore.cmd

restore.sh

README

MIT

# Machine Learning for .NET

[ML.NET](https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet) is a cross-platform open-source machine learning (ML) framework for .NET.

ML.NET allows developers to easily build, train, deploy, and consume custom models in their .NET applications without requiring prior expertise in developing machine learning models or experience with other programming languages like Python or R. The framework provides data loading from files and databases, enables data transformations, and includes many ML algorithms.

With ML.NET, you can train models for a [variety of scenarios](https://docs.microsoft.com/dotnet/machine-learning/resources/tasks), like classification, forecasting, and anomaly detection.

You can also consume both TensorFlow and ONNX models within ML.NET which makes the framework more extensible and expands the number of supported scenarios.

## Getting started with machine learning and ML.NET

- Learn more about the [basics of ML.NET](https://dotnet.microsoft.com/apps/machinelearning-ai/ml-dotnet).
- Build your first ML.NET model by following our [ML.NET Getting Started tutorial](https://dotnet.microsoft.com/learn/ml-dotnet/get-started-tutorial/intro).
- Check out our [documentation and tutorials](https://docs.microsoft.com/dotnet/machine-learning/).
- See the [API Reference documentation](https://docs.microsoft.com/dotnet/api/?view=ml-dotnet).
- Clone our [ML.NET Samples GitHub repo](https://github.com/dotnet/machinelearning-samples) and run some sample apps.
- Take a look at some [ML.NET Community Samples](https://github.com/dotnet/machinelearning-samples/blob/main/docs/COMMUNITY-SAMPLES.md).
- Watch some videos on the [ML.NET videos YouTube playlist](https://aka.ms/mlnetyoutube).

## Roadmap

Take a look at ML.NET's [Roadmap](ROADMAP.md) to see what the team plans to work on in the next year.

## Operating systems and processor architectures supported by ML.NET

ML.NET runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework.

ML.NET also runs on ARM64, Apple M1, and Blazor Web Assembly. However, there are some [limitations](docs/project-docs/platform-limitations.md).

64-bit is supported on all platforms. 32-bit is supported on Windows, except for TensorFlow and LightGBM related functionality.

## ML.NET NuGet packages status

[![NuGet Status](https://img.shields.io/nuget/vpre/Microsoft.ML.svg?style=flat)](https://www.nuget.org/packages/Microsoft.ML/)

## Release notes

Check out the [release notes](docs/release-notes) to see what's new. You can also read the [blog posts](https://devblogs.microsoft.com/dotnet/category/ml-net/) for more details about each release.

## Using ML.NET packages

First, ensure you have installed [.NET Core 2.1](https://www.microsoft.com/net/learn/get-started) or later. ML.NET also works on the .NET Framework 4.6.1 or later, but 4.7.2 or later is recommended.

Once you have an app, you can install the ML.NET NuGet package from the .NET Core CLI using:
```
dotnet add package Microsoft.ML
```

or from the NuGet Package Manager:
```
Install-Package Microsoft.ML
```

Alternatively, you can add the Microsoft.ML package from within Visual Studio's NuGet package manager or via [Paket](https://github.com/fsprojects/Paket).

Daily NuGet builds of the project are also available in our Azure DevOps feed:

> [https://pkgs.dev.azure.com/dnceng/public/_packaging/dotnet-libraries/nuget/v3/index.json](https://pkgs.dev.azure.com/dnceng/public/_packaging/dotnet-libraries/nuget/v3/index.json)

## Building ML.NET (For contributors building ML.NET open source code)

To build ML.NET from source please visit our [developer guide](docs/project-docs/developer-guide.md).

[![codecov](https://codecov.io/gh/dotnet/machinelearning/branch/main/graph/badge.svg?flag=production)](https://codecov.io/gh/dotnet/machinelearning)

| | Debug | Release |
|:---|----------------:|------------------:|
|**CentOS**|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Centos_x64_Net60&configuration=Centos_x64_Net60%20Debug_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Centos_x64_Net60&configuration=Centos_x64_Net60%20Release_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|
|**Ubuntu**|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Ubuntu_x64_Net60&configuration=Ubuntu_x64_Net60%20Debug_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Ubuntu_x64_Net60&configuration=Ubuntu_x64_Net60%20Release_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|
|**macOS**|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=MacOS_x64_Net60&configuration=MacOS_x64_Net60%20Debug_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=MacOS_x64_Net60&configuration=MacOS_x64_Net60%20Release_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|
|**Windows x64**|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x64_Net60&configuration=Windows_x64_Net60%20Debug_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x64_Net60&configuration=Windows_x64_Net60%20Release_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|
|**Windows FullFramework**|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x64_NetFx461&configuration=Windows_x64_NetFx461%20Debug_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x64_NetFx461&configuration=Windows_x64_NetFx461%20Release_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|
|**Windows x86**|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x86_Net60&configuration=Windows_x86_Net60%20Debug_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x86_Net60&configuration=Windows_x86_Net60%20Release_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|
|**Windows NetCore3.1**|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x64_Net60&configuration=Windows_x64_Net60%20Debug_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|[![Build Status](https://dev.azure.com/dnceng/public/_apis/build/status/dotnet/machinelearning/MachineLearning-CI?branchName=main&jobName=Windows_x64_Net60&configuration=Windows_x64_Net60%20Release_Build)](https://dev.azure.com/dnceng/public/_build/latest?definitionId=104&branchName=main)|

## Release process and versioning

Major releases of ML.NET are shipped once a year with the major .NET releases, starting with ML.NET 1.7 in November 2021 with .NET 6, then ML.NET 2.0 with .NET 7, etc. We will maintain release branches to optionally service ML.NET with bug fixes and/or minor features on the same cadence as .NET servicing.

Check out the [Release Notes](docs/release-notes) to see all of the past ML.NET releases.

## Contributing

We welcome contributions! Please review our [contribution guide](CONTRIBUTING.md).

## Community

- Join our community on [Discord](https://aka.ms/dotnet-discord).
- Tune into the [.NET Machine Learning Community Standup](https://dotnet.microsoft.com/live/community-standup) every other Wednesday at 10AM Pacific Time.

This project has adopted the code of conduct defined by the [Contributor Covenant](https://contributor-covenant.org/) to clarify expected behavior in our community.
For more information, see the [.NET Foundation Code of Conduct](https://dotnetfoundation.org/code-of-conduct).

## Code examples

Here is a code snippet for training a model to predict sentiment from text samples. You can find complete samples in the [samples repo](https://github.com/dotnet/machinelearning-samples).

```C#
var dataPath = "sentiment.csv";
var mlContext = new MLContext();
var loader = mlContext.Data.CreateTextLoader(new[]
 {
 new TextLoader.Column("SentimentText", DataKind.String, 1),
 new TextLoader.Column("Label", DataKind.Boolean, 0),
 },
 hasHeader: true,
 separatorChar: ',');
var data = loader.Load(dataPath);
var learningPipeline = mlContext.Transforms.Text.FeaturizeText("Features", "SentimentText")
 .Append(mlContext.BinaryClassification.Trainers.FastTree());
var model = learningPipeline.Fit(data);
```

Now from the model we can make inferences (predictions):

```C#
var predictionEngine = mlContext.Model.CreatePredictionEngine<SentimentData, SentimentPrediction>(model);
var prediction = predictionEngine.Predict(new SentimentData
{
 SentimentText = "Today is a great day!"
});
Console.WriteLine("prediction: " + prediction.Prediction);
```

## License

ML.NET is licensed under the [MIT license](LICENSE), and it is free to use commercially.

## .NET Foundation

ML.NET is a part of the [.NET Foundation](https://www.dotnetfoundation.org/projects).

MIT License Copyright (c) 2018 .NET Foundation Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.