MLOps pipeline using Docker Compose
Find a file
2024-03-02 08:55:39 -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 goals in readme 2024-02-20 20:09:32 -08:00
ROADMAP.md

Right now this is just a scratchpad. I'm converting my messy ML lab environment to something with better MLOps standards

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