New Release! Git-backed Machine Learning Model Registry for all your model management needs.
We have renamed Views to Projects in Iterative Studio.
Accordingly, Views dashboard is now called Projects dashboard; View settings are now called Project settings; and so on.
A project in Iterative Studio is an interactive representation of the information that your Git repository stores about your ML experiments and models.
When you connect to your Git repository from Iterative Studio, the Git commits and tags in the repository are parsed to identify all the data, metrics, hyperparameters and models. These values are then presented in an experiment table with each experiment (Git commit) in a row and the corresponding values for the data, metrics, hyperparameters and models in columns.
For Iterative Studio to extract the required values from your Git repositories, the values must be stored as described in the section about preparing your repositories.
A project
presents information stored in your Git repository in an interactive table.
All the projects that you have created are presented in a central projects dashboard. This dashboard opens up whenever you login to Iterative Studio.
All the
projects that you create are presented in a projects dashboard for easy access.
ML models across all your projects are presented in a Model Registry.
Within a project, you can:
In the following sections, you will see how to create, configure and share projects.