SEE ALSO: Concepts.

Anaconda Project
An encapsulation of your data science assets to make it easily portable. Anaconda Project automates setup, so you can quickly share and execute projects. All Project setup can be done from the Enterprise web interface.
Anaconda Project CLI
A command-line interface included with Anaconda Enterprise that allows data scientists to create and share channels and packages.
Anaconda Repository
A centralized location on your network for storing over 1,000 professionally built software packages for data science, from which the packages can be retrieved and installed.
A location in the repository where Anaconda Enterprise looks for packages.
Classic notebook
Refers to Jupyter Notebook, the previous version of the browser-based interactive development environment available in Anaconda Enterprise. It combines the notebook, file browser, text editor, terminal and outputs in one software product. See also the next-generation product, JupyterLab.
Making a set of local changes permanent by copying them to the remote server. Anaconda Enterprise checks to see if your work will conflict with the commits that your colleagues have made on the same project, so the files cannot be overwritten unless you so choose.
A deployed Anaconda Project. When you deploy a project, Enterprise finds and builds all of the software dependencies–the programs on which the Project depends in order to run–and encapsulates them so they are completely self- contained. This allows you to easily share the application with others.
Interactive data applications
Visualizations with sliders, drop-downs and other widgets that allow users to interact with them. Interactive data applications can drive new computations, update plots and connect to other programmatic functionality.
Interactive development environment (IDE)
A suite of software tools that combines everything a developer needs to write and test software. It typically includes a code editor, a compiler or interpreter and a debugger that the developer accesses through a single graphical user interface (GUI). An IDE may be installed locally, or it may be included as part of one or more existing and compatible applications accessed through a web browser.
The next-generation browser-based interactive development environment with flexible building blocks for interactive and collaborative computing. JupyterLab still contains the notebook, file browser, text editor, terminal and outputs in the same product. For classic Jupyter Notebook users, the interface for JupyterLab is familiar, but even more enjoyable and productive to work with.
Live notebooks
Together, JupyterLab and the classic Jupyter Notebooks are web-based IDE applications that allows you to create and share documents that contain live code, equations, visualizations and explanatory text.
Software files and information about the software, such as its name, the specific version and a description, that are bundled into a file that can be installed and managed by a package manager. Packages can then be encapsulated into Anaconda Projects for easy portability.
Project templates
When creating a new project, you can select a comprehensive project template that contains a set of packages and their dependencies. Choices are Anaconda 3.6 or 3.5, Anaconda 2, R language, SAS or Spark.
A common way to operationalize machine learning models is through REST APIs. REST APIs are callable URLs which provide results based on a query. This allows developers to make their applications intelligent without having to write models themselves.