Azure Data Science Virtual Machine 示例Samples on Azure Data Science Virtual Machines

Azure Data Science Virtual Machine (DSVM) 包含一整套示例代码。Azure Data Science Virtual Machines (DSVMs) include a comprehensive set of sample code. 这些示例包括用 Python 和 R 等语言写成的 Jupyter 笔记本和脚本。These samples include Jupyter notebooks and scripts in languages like Python and R.

备注

若要详细了解如何在 Data Science Virtual Machine 上运行 Jupyter 笔记本,请参阅访问 Jupyter 部分。For more information about how to run Jupyter notebooks on your data science virtual machines, see the Access Jupyter section.

先决条件Prerequisites

为了运行这些示例,必须预配 Ubuntu Data Science Virtual MachineIn order to run these samples, you must have provisioned an Ubuntu Data Science Virtual Machine.

可用示例Available samples

示例类别Samples category 说明Description 位置Locations
R 语言R language 示例介绍了多种方案,例如如何连接到基于 Azure 的云数据存储,以及如何比较开源 R 和 Microsoft Machine Learning Server。Samples illustrate scenarios such as how to connect with Azure-based cloud data stores and how to compare open-source R and Microsoft Machine Learning Server. 此外还介绍了如何在 Microsoft Machine Learning Server 和 SQL Server 上操作模型。They also explain how to operationalize models on Microsoft Machine Learning Server and SQL Server.
R 语言R language

~notebooks

~samples/MicrosoftR

~samples/RSqlDemo

~samples/SQLRServices

Python 语言Python language 示例介绍了多种方案,例如如何连接到基于 Azure 的云数据存储,以及如何使用 Azure 机器学习。Samples explain scenarios like how to connect with Azure-based cloud data stores and how to work with Azure Machine Learning.
Python 语言Python language

~notebooks

Julia 语言Julia language 详细说明了 Julia 中的绘图和深度学习。Provides a detailed description of plotting and deep learning in Julia. 此外还介绍了如何通过 Julia 调用 C 和 Python。Also explains how to call C and Python from Julia.
Julia 语言Julia language

Windows:Windows:
~notebooks/Julia_notebooks

Linux:Linux:
~notebooks/julia

Azure 机器学习Azure Machine Learning 介绍了如何使用机器学习生成机器学习和深度学习模型。Illustrates how to build machine-learning and deep-learning models with Machine Learning. 在任意位置部署模型。Deploy models anywhere. 使用自动化机器学习和智能超参数优化。Use automated machine learning and intelligent hyperparameter tuning. 还使用模型管理和分布式定型。Also use model management and distributed training.
机器学习Machine Learning

~notebooks/AzureML

PyTorch NotebookPyTorch notebooks 使用基于 PyTorch 的神经网络的深度学习示例。Deep-learning samples that use PyTorch-based neural networks. Notebook 从新手方案到高级方案都有涵盖。Notebooks range from beginner to advanced scenarios.
PyTorch NotebookPyTorch notebooks

~notebooks/Deep_learning_frameworks/pytorch

TensorFlowTensorFlow 使用 TensorFlow 框架实现的各种神经网络示例和技术。A variety of neural network samples and techniques implemented by using the TensorFlow framework.
TensorFlowTensorFlow

~notebooks/Deep_learning_frameworks/tensorflow

Microsoft 认知工具包Microsoft Cognitive Toolkit
由 Microsoft 的 Cognitive Toolkit 团队发布的深度学习示例。Deep-learning samples published by the Cognitive Toolkit team at Microsoft.
Cognitive ToolkitCognitive Toolkit

~notebooks/DeepLearningTools/CNTK/Tutorials

Linux:Linux:
~notebooks/CNTK

Caffe2Caffe2 使用基于 Caffe2 的神经网络的深度学习示例。Deep-learning samples that use Caffe2-based neural networks. 用户可通过多个笔记本熟悉 Caffe2 以及如何有效使用它。Several notebooks familiarize users with Caffe2 and how to use it effectively. 示例不仅包括图像预处理和数据集创建,Examples include image preprocessing and dataset creation. 还包括回归以及如何使用预定型模型。They also include regression and how to use pretrained models.
Caffe2Caffe2

~notebooks/Deep_learning_frameworks/caffe2

H2OH2O 基于 Python 的示例,使用 H2O 处理实际问题方案。Python-based samples that use H2O for real-world problem scenarios.
H2OH2O

~notebooks/h2o

SparkML 语言SparkML language 通过 pySpark 和 MMLSpark 使用 Apache Spark MLLib 工具箱功能的示例:面向 Apache Spark 2.x 上的 Apache Spark 的 Microsoft 机器学习。Samples that use features of the Apache Spark MLLib toolkit through pySpark and MMLSpark: Microsoft Machine Learning for Apache Spark on Apache Spark 2.x.
SparkML 语言SparkML language

~notebooks/SparkML/pySpark
~notebooks/MMLSpark

XGBoostXGBoost XGBoost 中的标准机器学习示例,用于分类、回归等场景。Standard machine-learning samples in XGBoost for scenarios like classification and regression.
XGBoostXGBoost

Windows:Windows:
\dsvm\samples\xgboost\demo


访问 JupyterAccess Jupyter

若要访问 Jupyter,请选择桌面或应用程序菜单中的 Jupyter 图标。To access Jupyter, select the Jupyter icon on the desktop or application menu. 还可以在 Linux 版的 DSVM 上访问 Jupyter。You also can access Jupyter on a Linux edition of a DSVM. 若要在 Web 浏览器中执行远程访问,请在 Ubuntu 上转到 https://<Full Domain Name or IP Address of the DSVM>:8000To access remotely from a web browser, go to https://<Full Domain Name or IP Address of the DSVM>:8000 on Ubuntu.

若要添加例外并允许通过浏览器访问 Jupyter,请使用以下指南:To add exceptions and make Jupyter access available over a browser, use the following guidance:

启用 Jupyter 异常

使用登录 Data Science Virtual Machine 所用的密码进行登录。Sign in with the same password that you use to log in to the Data Science Virtual Machine.

Jupyter 主页Jupyter home
Jupyter 主页Jupyter home

R 语言R language


R 示例

Python 语言Python language


Python 示例

Julia 语言Julia language


Julia 示例

Azure 机器学习Azure Machine Learning


Azure 机器学习示例

PyTorchPyTorch


PyTorch 示例

TensorFlowTensorFlow


TensorFlow 示例

CNTKCNTK


CNTK 示例

Caffe2Caffe2


caffe2 示例

H2OH2O


H2O 示例

SparkMLSparkML


SparkML 示例

XGBoostXGBoost


XGBoost 示例