ebonite 0.2.1

Machine Learning Lifecycle Framework

Ebonite is a machine learning lifecycle framework. It allows you to persist your models and reproduce them (as services or in general).

Installation

pip install ebonite

Quickstart

First, create a Ebonite client.

from ebonite import Ebonite
ebnt = Ebonite.local()

Second, create a task and push your model object with some sample data.

task = ebnt.get_or_create_task('my_project', 'my_task')
model = task.create_and_push_model(clf, test_x, 'my_sklearn_clf')

You are awesome! Now you can load you model from this repo and do other wonderful stuff with it, for example create a docker image.

Check out examples and documentation to learn more.

Documentation

… is available here

Supported libraries and repositories

• Machine Learning

  • scikit-learn

  • TensorFlow < 2

• Data

  • NumPy

  • pandas

  • images

• Repositories

  • SQLAlchemy

  • Amazon S3

• Serving

  • Flask

Contributing

Read this

Changelog

0.2.0 (2019-11-14)

• First release on PyPI.