Iterations
An iteration is a recurring work cycle within a phase, primarily used to log assets (models, datasets, graphs, and notes) to document the work and maintain transparency throughout an AI project.
Why use iterations?
Empower Data Scientists to achieve goals, evaluate results, and refine methods with feedback.
Facilitate informed decision-making, knowledge capture, and enhanced collaboration.
Ensure progress preservation, build trust in AI projects, and enable time-saving through efficient iterative developments.
Features | Description |
---|---|
Seamless creation via API | Iterations are exclusively created through the Vectice API |
Ownership and asset logging | Each iteration has an owner who solely can log assets via the Vectice API |
Starred iterations | Iterations can be highlighted with a star to signify their importance, drawing attention to key assets or information within the iteration. |
Organize iteration work | Users can organize iterations into sections within the Vectice app, allowing for a tailored presentation of their iteration progress and the work completed. |
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