MLeap Framework

An MLeap Framework is a machine learning framework for deploying machine learning pipelines.

• See: Pipeline.AI, MLeap Execution Engine, MLeap Serialization Format, MLflow.

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References

2018

• https://github.com/combust/mleap
  • QUOTE: MLeap allows data scientists and engineers to deploy machine learning pipelines from Spark and Scikit-learn to a portable format and execution engine.

    ... Using the MLeap execution engine and serialization format, we provide a performant, portable and easy-to-integrate production library for machine learning data pipelines and algorithms. For portability, we build our software on the JVM and only use serialization formats that are widely-adopted. ...

    Our goals for this project are:

    • Allow Researchers/Data Scientists and Engineers to continue to build data pipelines and train algorithms with Spark and Scikit-Learn
    • Extend Spark/Scikit/TensorFlow by providing ML Pipelines serialization/deserialization to/from a common framework (Bundle.ML)
    • Use MLeap Runtime to execute your pipeline and algorithm without dependencies on Spark or Scikit (numpy, pandas, etc)

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