Rapid Analytics & Model Prototyping

The developer documentation

RAMP packages

RAMP packages offer versatile tools to define, build and optimize machine learning workflows via data challenges, great for prototyping models in your data science team.

RAMP workflow

RAMP workflow allows you to formalise a machine learning workflow by defining score types (metrics), workflow elements and prediction types.

RAMP board

RAMP board consists of a bundle of modules that allow you to easily setup your own RAMP server and deploy new data challenges.

Install RAMP bundle

All RAMP packages are available on PyPI and can be easily installed using pip

$ pip install ramp-workflow ramp-frontend ramp-database ramp-engine ramp-utils

The RAMP ecosystem contains two organizations and two libraries. The purpose of the bundle is to define, build, manage, and optimize data analytics workflows, typically on the top of open source machine learning libraries like pandas, scikit-learn, and keras. The bundle consists of

Library/Organisation Purpose Publicly available
ramp-workflow A set of reusable tools and scripts to define score types (metrics), workflow elements, prediction types and data connectors.
ramp-board A library managing the frontend and the database of the RAMP platform.
ramp-data An organization containing data sets on which workflows are trained and evaluated.
ramp-kits An organization containing starting kits that use tools from ramp-workflow to implement a first valid (tested) workflow.

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