Diffgram has two frameworks for developing.
Both frameworks unlock a growing ecosystem of ML programs, provide opinionated development options, and standard ways to install other tools.
Examples of areas include:
- Interaction with an Ecosystem of tech
- ML Modeling
- ML Programs (Such as sampling, filtering)
- Training Data Orchestration
- Human task workflow
- Surfacing your Training Data Processes
- QA Assurance programs
- ML Maintenance
Both frameworks are in "Preview" on our Quality Bar Status.
We encourage you to try them out and share your insights with the community.
Please note the SDK, CLI, etc. are considered part of the standard ecosystem and interact with frameworks.
The baseline configuration supports anything that can be reasonably implemented or configured directly.
Frameworks are more open ended, in that you can integrate or install 3rd party programs, write your own programs that integrate, or extend functions etc. Frameworks are opinionated.
Components are open further, allowing you to develop custom software that uses existing Diffgram technical components, such as JS classes, Vue components, etc.
Over time we expect these frameworks will further integrate with each other, and other diffgram development options.
Updated 11 months ago