An open source library to add BigML models to the MLFlow API
Project description
BigMLFlow
This library defines the connectors needed for the integration and deployment of BigML models using MLFlow.
Introduction
All the resources generated by the BigML
API-first platform, including
models, are totally white-box, and they can be downloaded as JSON and used
to predict anywhere. The bigmlflow
library uses
BigML's Python bindings
to integrate with MLFlow
tracking and deploying capacities.
The examples/README.md file shows a few use cases
that cover some of the Supervised Models available in BigML and
a full training example to demo the logging and tracking of BigML's models
using MLFlow
.
Installation
This library is available as a PyPI package. To install it, just run:
pip install bigmlflow
Tests
The tests
directory contains some tests for the logging of models.
We use Pytest
to run the tests, so you can install it separately
pip install pytest
or as an extra for development and testing purposes
pip install -e .[tests]
How to Contribute
Please follow the next steps:
- Fork the project on github.com.
- Create a new branch.
- Commit changes to the new branch.
- Send a pull request.
.. :changelog:
History
1.0.2 (2022-11-29)
- Adding documentation and updating MLFlow version.
1.0.1 (2022-11-02)
- Adding MANIFEST.in file to fix the distribution file.
1.0.0 (2022-10-19)
- First version of the library.
Project details
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