MLFairy aims to give CoreML developers the tools necessary to create amazing models. We want to complete the workflow loop between training and deployment of models by addressing the following two pain points:
- How do I ensure my users have the best experience in my app with the latest version of my CoreML model?
- How to get real-world data to improve my CoreML model during training?
MLFairy's strives to address these concerns with three pillars:
- Simple deployment of CoreML models.
- Automatic collection of prediction data.
- Secure everything with encryption.
If you're interested in knowing more, follow along with the docs, or jump to the section you're most interested in.