intel/intel-optimized-ml
intel
用于在Intel®架构上运行机器学习工作负载的容器，包含Intel® Scikit-learn扩展和XGBoost，优化了在Intel硬件上的训练和推理性能。
6 次收藏下载次数: 0状态：社区镜像维护者：intel仓库类型：镜像最近更新：1 年前
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https://xuanyuan.cloud/agents.md
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【项目不再积极管理】此镜像仓库将不再由Intel维护。
Intel® 优化的机器学习
Intel® Scikit-learn扩展（Intel® Extension for Scikit-learn*）通过加速Intel®硬件上的机器学习模型训练和推理，提升了Scikit-learn*的性能。
XGBoost*是一个优化的分布式梯度提升库，设计高效、灵活且可移植。
镜像
以下镜像包含Intel® Scikit-learn扩展和XGBoost：
| 标签(s) | Intel SKLearn | Scikit-learn | XGBoost | Dockerfile |
|---|---|---|---|---|
2024.7.0-pip-base, latest | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.7.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.2 | https://github.com/dmlc/xgboost/releases/tag/v2.1.1 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.6.0-pip-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.6.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.0 | https://github.com/dmlc/xgboost/releases/tag/v2.1.0 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.5.0-pip-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.5.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.0 | https://github.com/dmlc/xgboost/releases/tag/v2.1.0 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.3.0-pip-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.3.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.4.2 | https://github.com/dmlc/xgboost/releases/tag/v2.0.3 | https://github.com/intel/ai-containers/blob/v0.4.0-Beta/classical-ml/Dockerfile |
2024.2.0-xgboost-2.0.3-pip-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.2.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.4.1 | https://github.com/dmlc/xgboost/releases/tag/v2.0.3 | https://github.com/intel/ai-containers/blob/v0.4.0-Beta/classical-ml/Dockerfile |
scikit-learning-2024.0.0-xgboost-2.0.2-pip-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.0.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.3.2 | https://github.com/dmlc/xgboost/releases/tag/v2.0.2 | https://github.com/intel/ai-containers/blob/v0.3.4/classical-ml/Dockerfile |
以下镜像额外包含Jupyter Notebook服务器：
| 标签(s) | Intel SKLearn | Scikit-learn | XGBoost | Dockerfile |
|---|---|---|---|---|
2024.7.0-pip-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.7.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.2 | https://github.com/dmlc/xgboost/releases/tag/v2.1.1 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.6.0-pip-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.6.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.1 | https://github.com/dmlc/xgboost/releases/tag/v2.1.1 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.5.0-pip-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.5.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.0 | https://github.com/dmlc/xgboost/releases/tag/v2.1.0 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.3.0-pip-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.3.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.4.2 | https://github.com/dmlc/xgboost/releases/tag/v2.0.3 | https://github.com/intel/ai-containers/blob/v0.4.0-Beta/classical-ml/Dockerfile |
2024.2.0-xgboost-2.0.3-pip-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.2.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.4.1 | https://github.com/dmlc/xgboost/releases/tag/v2.0.3 | https://github.com/intel/ai-containers/blob/v0.4.0-Beta/classical-ml/Dockerfile |
scikit-learning-2024.0.0-xgboost-2.0.2-pip-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.0.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.3.2 | https://github.com/dmlc/xgboost/releases/tag/v2.0.2 | https://github.com/intel/ai-containers/blob/v0.3.4/classical-ml/Dockerfile |
运行Jupyter容器
bashdocker run -it --rm \ -p 8888:8888 \ --net=host \ -v $PWD/workspace:/workspace \ -w /workspace \ docker.xuanyuan.run/intel/intel-optimized-ml:2024.2.0-xgboost-2.0.3-pip-jupyter
运行上述命令后，将URL（类似http://127.0.0.1:$PORT/?token=）复制到浏览器中以访问Notebook服务器。
包含Intel® Python发行版的镜像
以下镜像包含Intel® Python发行版（Intel® Distribution for Python*）：
| 标签(s) | Intel SKLearn | Scikit-learn | XGBoost | Dockerfile |
|---|---|---|---|---|
2024.7.0-idp-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.7.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.2 | https://github.com/dmlc/xgboost/releases/tag/v2.1.1 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.6.0-idp-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.6.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.1 | https://github.com/dmlc/xgboost/releases/tag/v2.1.1 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.5.0-idp-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.5.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.0 | https://github.com/dmlc/xgboost/releases/tag/v2.1.0 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.3.0-idp-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.3.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.4.1 | https://github.com/dmlc/xgboost/releases/tag/v2.1.0 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.2.0-xgboost-2.0.3-idp-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.2.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.4.1 | https://github.com/dmlc/xgboost/releases/tag/v2.0.3 | https://github.com/intel/ai-containers/blob/v0.4.0-Beta/classical-ml/Dockerfile |
scikit-learning-2024.0.0-xgboost-2.0.2-idp-base | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.0.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.3.2 | https://github.com/dmlc/xgboost/releases/tag/v2.0.2 | https://github.com/intel/ai-containers/blob/v0.3.4/classical-ml/Dockerfile |
以下镜像额外包含Jupyter Notebook服务器：
| 标签(s) | Intel SKLearn | Scikit-learn | XGBoost | Dockerfile |
|---|---|---|---|---|
2024.7.0-idp-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.7.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.2 | https://github.com/dmlc/xgboost/releases/tag/v2.1.1 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.6.0-idp-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.6.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.1 | https://github.com/dmlc/xgboost/releases/tag/v2.1.1 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.5.0-idp-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.5.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.5.0 | https://github.com/dmlc/xgboost/releases/tag/v2.1.0 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.3.0-idp-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.3.0 | [v1.4.0] | https://github.com/dmlc/xgboost/releases/tag/v2.1.0 | https://github.com/intel/ai-containers/blob/v0.4.0/classical-ml/Dockerfile |
2024.2.0-xgboost-2.0.3-idp-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.2.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.4.1 | https://github.com/dmlc/xgboost/releases/tag/v2.0.3 | https://github.com/intel/ai-containers/blob/v0.4.0-Beta/classical-ml/Dockerfile |
scikit-learning-2024.0.0-xgboost-2.0.2-idp-jupyter | https://github.com/intel/scikit-learn-intelex/releases/tag/2024.0.0 | https://github.com/scikit-learn/scikit-learn/releases/tag/1.3.2 | https://github.com/dmlc/xgboost/releases/tag/v2.0.2 | https://github.com/intel/ai-containers/blob/v0.3.4/classical-ml/Dockerfile |
从源代码构建
要从源代码构建镜像，请克隆AI Containers仓库（https://github.com/intel/ai-containers），按照主README.md文件设置环境，然后运行以下命令：
bashcd classical-ml docker compose build ml-base docker compose run ml-base
以下是组中每个容器的服务列表：
| 服务名称 | 描述 |
|---|---|
ml-base | 包含Intel® Scikit-learn扩展和XGBoost的基础镜像 |
jupyter | 添加Jupyter Notebook服务器 |
许可证
查看Intel® Python发行版的许可证（https://github.com/intel/ai-containers/blob/main/LICENSE）。
以下镜像还包含其他软件，可能受其他许可证约束（如基础镜像中的Pytorch*、Jupyter*、Bash等）。
镜像用户有责任确保对以下镜像的任何使用都符合其中包含的所有软件的相关许可证。
* 其他名称和品牌可能是他人的财产。
镜像拉取方式
您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本，请访问 标签列表页面。
轩辕镜像加速拉取命令点我查看更多 intel-optimized-ml 镜像标签
docker pull docker.xuanyuan.run/intel/intel-optimized-ml:<标签>
DockerHub 原生拉取命令
docker pull intel/intel-optimized-ml:<标签>
镜像拉取常见问题
功能
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用户好评
来自真实用户的反馈，见证轩辕镜像的优质服务
oldzhang
运维工程师
Linux服务器
5
"Docker访问体验非常流畅，大镜像也能快速完成下载。"