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technical-observability-for-ml
technical-observability-for-ml PublicThis is an example how observability can be achieved in a technical sense with ML-Models
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mlflow-docker
mlflow-docker PublicThis repository contains a Docker-Setup for MLflow with integrated authentication and MinIO + PostgreSQL storage
Dockerfile
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feast-entity-store
feast-entity-store PublicAn extension for Feast (Feature Store) to support feature retrieval from MinIO without knowing the exact Entity-IDs
Python
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bentoml-deployment-coordinator
bentoml-deployment-coordinator PublicA webservice that provides endpoints to manage ML-model deployments via BentoML in tmux-sessions or Docker containers
Python
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