From the webpage:
Start doing data science in minutes
As a data scientist, you don’t want to waste your time installing software. Our goal is to provide a virtual environment that will enable you to start doing data science in a matter of minutes.
As a teacher, author, or organization, making sure that your students, readers, or members have the same software installed is not straightforward. This open source project will enable you to easily create custom software and data bundles for the Data Science Toolbox.
A virtual environment for data science
The Data Science Toolbox is a virtual environment based on Ubuntu Linux that is specifically suited for doing data science. Its purpose is to get you started in a matter of minutes. You can run the Data Science Toolbox either locally (using VirtualBox and Vagrant) or in the cloud (using Amazon Web Services).
We aim to offer a virtual environment that contains the software that is most commonly used for data science while keeping it as lean as possible. After a fresh install, the Data Science Toolbox contains the following software:
- Python, with the following packages: IPython Notebook, NumPy, SciPy, matplotlib, pandas, scikit-learn, and SymPy.
- R, with the following packages: ggplot2, plyr, dplyr, lubridate, zoo, forecast, and sqldf.
- dst, a command-line tool for installing additional bundles on the Data Science Toolbox (see next section).
Let us know if you want to see something added to the Data Science Toolbox.
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Great resource for doing or teaching data science!
And an example of using a VM to distribute software in a learning environment.