Please see our complete documentation at http://mleap-docs.combust.ml.

MLeap deploys Spark ML (and some MLlib) transformers and pipelines to production without a Spark Context.

MLeap extends scikit-learn's functionality to be able to serialize and deploy scikit transformers, pipelines and feature unions without any dependencies on scikit (numpy, scipy, c++ libraries). It also serializes transformers and pipelines as Spark, so you can load and deploy your scikit pipelines on Spark infrastructure with a few lines of code.

• Serializing a Spark ML Pipeline and Serving with MLeap
• Setting up a Spark 2.0 notebook with MLeap and Toree
• Setting up PySpark 2.0 notebook with MLeap and Toree
• Setting up Scikit-Learn with MLeap

• ML Pipelines with AirBnb data - Scala
• ML Pipelines with AirBnb data - PySpark
• ML Pipelines with Lending Club data - Scala