Simple data science experimentation with jupyter, papermill, and mlflow
Associated blog post: A simpler experimentation workflow with Jupyter, Papermill, and MLflow
- Clone this repo
git clone [email protected]:eugeneyan/papermill-mlflow.git
- Set up virtualenv
cd papermill-mlflow
# Create virtualenv based on requirements.txt
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# Install kernelspec for Jupyter notebooks (the name argument must be identical)
python -m ipykernel install --user --name=papermill-mlflow
- Start Jupyter notebook
cd notebooks
jupyter notebook
- Run the cells in
runner.ipynb
- Start MLflow (in another terminal)
# Open another terminal
# Activate the virtualenv
cd papermill-mlflow
source venv/bin/activate
# Start the mlflow server
cd notebooks
mlflow server
- Access the MLflow UI opening this in a browser: http://127.0.0.1:5000
- Navigate to "indices" in the experiment tab if necessary
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