#Python

The facial recognition has become the most popular method for validating people's identities, thus enabling access to systems, confirmation of personal and documentary data, and approval of actions and documents.
The challenges are related to performance when the database is very large, accuracy, and especially the privacy of biometric facial data. For these challenges, nothing is better than using InterSystems Vector Search, as it allows:

1. Performing vector searches in millions of records with much faster responses than traditional methods.
2. The vector and mathematical models used by Vector Search

Hello everyone,
I’m looking to implement Continuous Training (CT) as part of an MLOps strategy for some data science projects in IRIS. I want to automate the full cycle:

- Monitoring model performance & accuracy degradation.
- Retraining models automatically.
- Validating and updating production models.

I’ve looked into IntegratedML, but it seems more focused on the SQL interface for training (AutoML). Even with the new Custom Models (beta), which allows for more flexibility with Python, it doesn't seem to provide the "Continuous" orchestration out of the box.

I’d like to know: