Elefant is an open source software platform for the Machine Learning community developed using Python. It is a platform for quick prototyping and deploying machine learning algorithms and building the end applications rapidly. Elefant includes modules for many common optimization problems arising in machine learning and inference.

The key feature of Elefant is its lightweight component based design. Its design allows reuse of various components within the Elefant framework and provides a mechanism to inter-operate or easily integrate with external software systems.

Its easy to use graphical user interface allows quick prototyping or testing of new machine learning algorithms and also scripting API interface in python provides advance application development.

The diagram below illustrates the high-level system view of Elefant framework.

The Reference Guide for Component Based Framework and Components of Elefant document contains information for developing applications using programming interface (scripting and GUI) of Elefant. It also provides detailed information about internal system design of this framework, various components like data, algorithms, model selection and visualization components and its usage. This document is useful for both application and system developers.

The source documentation for the various packages, modules, classes and their hierarchy is available at Elefant API documentation. The source documentation is generated by Doxygen.

The Elefant Manual document provides information about core Elefant modules developed in python.

The PyPetsc User Reference Manual provides information on how to use the PyPetsc package in your Python scripts.