dockerignore is ignored

Running mlflow projects in the docker environment does not honour .dockerignore.

This has been an outstanding issue on mlflow for a long time and does not appear to be progressing. We should look at alternatives for running projects. Options:

1. plain python execution with venv
- advantage - simple
- disadvantage - uncontrolled
2. docker run script as entrypoint
- advantage - controlled, most similar to the current method
- disadvantage - requires some (minor?) MLOps rework, do we lose any of the mlflow project features?

I'm leaning towards option 2 as this offers the best compatibility with existing work. Please feel free to suggest any alternatives or opinions below.

related to #132