Explore Azure Machine Learning with Jupyter Notebooks (v1)

APPLIES TO: Python SDK azureml v1

The Azure Machine Learning Notebooks repository includes Azure Machine Learning Python SDK (v1) samples. These Jupyter notebooks are designed to help you explore the SDK and serve as models for your own machine learning projects. In this repository, you'll find tutorial notebooks in the tutorials folder and feature-specific notebooks in the how-to-use-azureml folder.

This article shows you how to access the repositories from the following environments:

  • Azure Machine Learning compute instance
  • Bring your own notebook server
  • Data Science Virtual Machine

The easiest way to get started with the samples is to complete the Quickstart: Get started with Azure Machine Learning. Once completed, you'll have a dedicated notebook server pre-loaded with the SDK and the Azure Machine Learning Notebooks repository. No downloads or installation necessary.

To view example notebooks: 1. Sign in to studio and select your workspace if necessary. 1. Select Notebooks. 1. Select the Samples tab. Use the SDK v1 folder for examples using Python SDK v1.

Option 2: Access on your own notebook server

If you'd like to bring your own notebook server for local development, follow these steps on your computer.

  1. Use the instructions at Azure Machine Learning SDK to install the Azure Machine Learning SDK (v1) for Python

  2. Create an Azure Machine Learning workspace.

  3. Write a configuration file file (aml_config/config.json).

  4. Clone the Machine Learning Notebooks repository.

    git clone https://github.com/Azure/MachineLearningNotebooks.git --depth 1
    
  5. Start the notebook server from the directory containing your clone.

    jupyter notebook
    

These instructions install the base SDK packages necessary for the quickstart and tutorial notebooks. Other sample notebooks may require you to install extra components. For more information, see Install the Azure Machine Learning SDK for Python.

Option 3: Access on a DSVM

The Data Science Virtual Machine (DSVM) is a customized VM image built specifically for doing data science. If you create a DSVM, the SDK and notebook server are installed and configured for you. However, you'll still need to create a workspace and clone the sample repository.

  1. Create an Azure Machine Learning workspace.

  2. Add a workspace configuration file using either of these methods:

    Download config.json

  3. From the directory where you added the configuration file, clone the Machine Learning Notebooks repository.

    git clone https://github.com/Azure/MachineLearningNotebooks.git --depth 1
    
  4. Start the notebook server from the directory, which now contains the clone and the config file.

    jupyter notebook
    

Next steps

Explore the MachineLearningNotebooks repository to discover what Azure Machine Learning can do.

For more GitHub sample projects and examples, see these repos: