ML evaluation and logging platform for healthcare
Project description
Argos Tracker Getting Started
- Clone Repo
- Make sure Anaconda is installed
- Create conda env with
conda env create --name argos-tracker --file=environment.yml - To update previously created envs use
conda env update --file environment.yml --prune
Jupyter Lab
- Activate conda env with
conda activate argos-tracker - Create project specific ipykernel if it has not been created yet:
python -m ipykernel install --user --name argos-tracker --display-name "argos-tracker"
- Start jupyter lab:
jupyter lab - Open client using link provided on start
- Open test_notebook_mimic.ipynb and select the argos-tracker ipykernel
MLflow
- Open a new terminal window and activate the argos-tracker env
- Start mlflow:
mlflow server --host 127.0.0.1 --port 8787 --app-name mlflow_cors
Argos Dashboard
- In a third terminal window activate the argos-tracker env
- Go to the reports_dashboard directory
cd reports_dashboard - Run
npm cito install dependencies for Vue frontend - The following error may occur if using ubuntu with a version older than 24.04:
node: /lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.31' not found (required by /home/user/anaconda3/envs/argos-tracker/bin/../lib/libnode.so.127)
- Start client with
npm run dev
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