ml-base is a package that provides base classes and utilities that are useful for deploying machine learning models.
The easiest way to install ml-base is using pip
pip install ml-base
There are several examples of how to use the ml-base framework in the documentation.
First, download the source code with this command:
git clone https://github.com/schmidtbri/ml-base
Then create a virtual environment and activate it:
# go into the project directory
cd ml-base
make venv
source venv/bin/activate
Install the dependencies:
make dependencies
To run the unit test suite execute these commands:
# first install the test dependencies
make test-dependencies
# run the test suite
make test
# clean up the unit tests
make clean-test
FAQs
Base classes and utilities that are useful for deploying ML models.
We found that ml-base demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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