Samples on Azure Data Science Virtual Machines

Article
06/18/2021

Azure Data Science Virtual Machines (DSVMs) include a comprehensive set of sample code. These samples include Jupyter notebooks and scripts in languages like Python and R.

Note

For more information about how to run Jupyter notebooks on your data science virtual machines, see the Access Jupyter section.

Prerequisites

In order to run these samples, you must have provisioned an Ubuntu Data Science Virtual Machine.

Available samples

Samples category	Description	Locations
Python language	Samples explain scenarios like how to connect with Azure-based cloud data stores and how to work with Azure Machine Learning. Python language	`~notebooks`
Julia language	Provides a detailed description of plotting and deep learning in Julia. Also explains how to call C and Python from Julia. Julia language	Windows: `~notebooks/Julia_notebooks` Linux: `~notebooks/julia`
Azure Machine Learning	Illustrates how to build machine-learning and deep-learning models with Machine Learning. Deploy models anywhere. Use automated machine learning and intelligent hyperparameter tuning. Also use model management and distributed training. Machine Learning	`~notebooks/AzureML`
PyTorch notebooks	Deep-learning samples that use PyTorch-based neural networks. Notebooks range from beginner to advanced scenarios. PyTorch notebooks	`~notebooks/Deep_learning_frameworks/pytorch`
TensorFlow	A variety of neural network samples and techniques implemented by using the TensorFlow framework. TensorFlow	`~notebooks/Deep_learning_frameworks/tensorflow`
H2O	Python-based samples that use H2O for real-world problem scenarios. H2O	`~notebooks/h2o`
SparkML language	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 language	`~notebooks/SparkML/pySpark` `~notebooks/MMLSpark`
XGBoost	Standard machine-learning samples in XGBoost for scenarios like classification and regression. XGBoost	Windows: `\dsvm\samples\xgboost\demo`

Access Jupyter

To access Jupyter, select the Jupyter icon on the desktop or application menu. You also can access Jupyter on a Linux edition of a DSVM. To access remotely from a web browser, go to https://<Full Domain Name or IP Address of the DSVM>:8000 on Ubuntu.

To add exceptions and make Jupyter access available over a browser, use the following guidance:

Enable Jupyter exception