fastscore/model-deploy repository overview

⁠FastScore Deploy

FastScore Deploy provides Data Scientists native integrations to many of their favorite workbenches and model creation tools like Jupyter Notebooks. With Deploy it’s simple to create and test model assets for production, before the model leaves the Data Scientists’ desk.

Please visit the FastScore Deploy Product Manual⁠ for a detailed review of how to get FastScore Manage up and running.

This is a containerized, Jupyter-friendly version of the FastScore SDK, built on top of the Jupyter Data Science stack. You can run it with:

docker run -it --rm -p 8888:8888 --net="host" fastscore/model-deploy:dev

There are four example notebooks in the default working directory: one each for Python2, Python3, R, and PFA/PrettyPFA models.

To make full use of the FastScore Jupyter integration, you'll need to also have a FastScore fleet running and accessible; see Jupyter Notebook Data Science Stack⁠ for more details.