Comments (1)
Actually will just use virtual environments for now.
from toy-ml-pipeline.
Related Issues (20)
- Abstract `io` to work with any s3 bucket HOT 1
- Abstract `models` to move the random forest subclass to the actual training dir HOT 1
- Add evaluation to training script
- `id` examples in the data HOT 1
- New thought but idk how to scope / refactor codebase for this
- add type hints for model class
- Make diagram HOT 1
- Write README and documentation HOT 1
- Modify training script to train model on many months of data
- Make an inference pipeline
- Improve on current model
- Better cleaning logic
- Incorporate JupyterLab functionality
- Write a notebook to explore the data
- Dockerize
- Rewrite ETL in spark
- Write a script to run all the components
- Edit readme to remove references to makefile
- Problems running the pipeline HOT 1
- .env files are missing and docker run doesn't work
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