MLFlow Streamlit Interaction

Motivation

In this repo I bring together my favorite two Python libraries right now: streamlit and mlflow. It is a simple demonstration of how you can use streamlit to experiment with various machine learning models and mlflow to keep track of your experiments.

Watch this YouTube video for a simple demonstration:

Try yourself

Step 1: Clone this repository to your local machine

git clone git@github.com:mwinterde/mlflow-with-streamlit.git

Step 2: Build docker containers for the streamlit and mlflow services.

docker-compose build

Step 3: Run the services.

docker-compose up

Step 4: Explore.

• Open http://localhost:8501 to interact with the streamlit app.
• Open http://localhost:5000 to access the mlflow user interface.