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.
Upon completion of this lab playground, you will be able to:
This lab is intended for:
You should be familiar with:
Luke is a Site Reliability Engineer at Microsoft. His background is infrastructure development using Terraform and in 2021 he was awarded the HashiCorp Ambassador award. He is an Azure DevOps Engineer Expert, Azure Administrator Associate, and HashiCorp Certified - Terraform Associate.