Mlflow on MinIO and docker

1. Ensure you have a docker/config.env with the necessary config keys (any ${VARIABLE} in the docker/docker-compose.yml file)

2. tasks/docker-start.sh

3. Configure connection credentials

   1. PostgreSQL credentials

      1. Ensure the new postgresql instance has a user for the optuna db and a different one for the mlflow db
      2. Create a new database called optuna and another called mlflow (if they don't already exist)

   2. MinIO credentials

      1. create a new access key either using mc CLI client or the console terminal (usually found at localhost:9001)
      2. create a new bucket called mlflow

   3. Update docker/config.env with the newly-updated credentials

   4. docker-compose down and repeate step 2.

   5. Update connection variables in create_study.py

4. python -m pip install -r requirements.txt

5. python run_trials.py

6. Check run in mlflow tracking URL