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Build and share code via Azure Notebooks
An Azure service enables enterprises to host Jupyter Notebooks in the cloud to ease access and management. Learn whether it could benefit your dev team, and how to get started.
Jupyter Notebooks offer a way to share executable code and other information via an open source, browser-based...
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web application. But while they've gained momentum in the developer and data science communities, Jupyter Notebooks can sometimes be a challenge to install and manage.
To make the technology more broadly accessible, Microsoft offers Azure Notebooks.
Azure Notebooks is a hosted service that enterprises can use to develop and run Jupyter Notebooks in the cloud, without having to install any software. It is targeted at data scientists, developers and students who want to run code in a browser using Python 2, Python 3, R and F#.
The service provides a diverse set of features for users that range from hobbyist programmers needing a sandbox to those who will deliver training to hundreds of students. Potential use cases for Azure Notebooks include:
- Teachers can deliver an Intro to Python Programming class.
- Data scientists can gain access to an Anaconda environment to practice Python and R data science and machine learning.
- Webinar hosts and conference speakers can provide interactive demonstrations through notebooks embedded in PowerPoint presentations.
Users who sign into the service with an account associated with an Azure subscription can take advantage of Microsoft's Linux Data Science Virtual Machines (DSVMs) to run their notebooks. DSVMs are Azure virtual machine images pre-configured with popular tools that are commonly used for data analytics, machine learning and AI training.
As one of the biggest uses for Azure Notebooks is classroom learning, Microsoft has recently given instructors the ability to enable student access to DSVMs that they've deployed in their existing Azure subscriptions.
When you create an Azure Notebook, you must select a runtime environment. This is typically referred to as a kernel, but you can think of it as the platform that will execute code under the hood. Microsoft kernel offerings currently provide a few different versions of Python and Anaconda, along with R and F#.
On top of the base runtime environment, Microsoft provides pre-installed packages for data scientists, but users can also choose to install their own packages for supported languages. They can share Azure Notebooks and enable read access to anyone on the internet. Users who sign up and login will have the ability to create, update and run their own notebooks.
The best way to learn Azure Notebooks is to get real-world exposure to the service. Microsoft offers several step-by-step guides to help users perform tasks, such as setting up an ID to save work, sharing notebooks with others, and creating code cells to embed executable Python code.