MLOps pipeline using Docker Compose
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2024-03-02 09:11:52 -08:00
jupyter Use nvidia tensorflow image; check NUMA settings 2024-03-02 08:55:39 -08:00
.gitignore Setting the CUDA toolkit to match my host OS 2024-02-22 18:54:49 -08:00
docker-compose.yaml Use nvidia tensorflow image; check NUMA settings 2024-03-02 08:55:39 -08:00
Makefile Use nvidia tensorflow image; check NUMA settings 2024-03-02 08:55:39 -08:00
README.md Update README 2024-03-02 09:11:52 -08:00
ROADMAP.md Initial version -- can create a jupyter lab container 2024-02-19 19:48:10 -08:00

#MLOps

I have an ML lab environment at home that I'm converting to something with better MLOps standards

WORK IN PROGRESS

Insert tacky animated gif of a construction worker here

Goals

Broadly, the goals are:

  • Local dev environment that's as similar as possible to production
  • A managed Jupyter Lab environment for experimentation
  • Do something sensible with features and feature extraction
  • A good mockup of an operationalized model
  • CI/CD pipeline with local access to test/verification

Requirements