/ Machine Learning

A machine learning lifecycle framework

A machine learning lifecycle framework

ebonite

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.

Supported libraries and repositories

  • Machine Learning

    • scikit-learn

    • TensorFlow < 2

    • XGBoost

    • LightGBM

    • PyTorch

    • CatBoost

  • Data

    • NumPy

    • pandas

    • images

  • Repositories

    • SQLAlchemy

    • Amazon S3

  • Serving

    • Flask

GitHub