Azure Notebooks enables data scientists and machine learning engineers to build and deploy models using Jupyter notebooks from within the Azure ML Workspace. A full Jupyter notebook environment is hosted in the cloud and provides access to an entire Anaconda environment. The tedious task of set up and installing all the tools for a data science environment is automated. Data scientists, teachers, and students can dive right into learning without spending time installing software. 

The Azure Machine Learning Notebooks repository contains samples and tutorials using the Azure Machine Learning SDK with Python or R. These samples are a great way to explore and learn the SDK capabilities, which enables data scientists to use cloud-hosted services to speed up development.

The playground is a safe and secure sandbox environment for you to explore your own ideas, follow along with Cloud Academy courses, or answer your own questions all without the need to install any software on your local machine. You will use Azure Notebooks and launch a Jupyter notebook sample from the repository to explore using the Azure Machine Learning SDK to create experiments and train models.

Learning Objectives

Upon completion of this lab playground, you will be able to:

• Explore the benefits of using an Azure Notebook
• Create a compute instance to host an Azure Notebook
• Create and run Azure Notebooks
• Use the Azure Machine Learning SDK to perform machine learning tasks

Intended Audience

This lab is intended for:

• Individuals studying to take the Azure DP-100 exam
• Anyone interested in learning how to use the Azure Machine Learning SDK
• Students interested in data science

Lab Prerequisites

You should be familiar with:

• Basic concepts of Azure Machine Learning
• Experience with Python or R is not required but preferred.