Modular toolkit for Data Processing (MDP): a Python data processing framework

• Published in: Frontiers in neuroinformatics Vol. 2; p. 8
• Main Author: Zito, Tiziano
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 2008; Frontiers Media S.A
• Subjects: Algorithms; Application programming interface; computational neuroscience; Data processing; International conferences; Learning algorithms; Library collections; machine learning; Memory; Modular toolkit for Data Processing; Nervous system; Neural networks; Neuroscience; Neurosciences; python; Software; Germany; computational neuroscience; Modular toolkit for Data Processing; machine learning; Python
• ISSN: 1662-5196; 1662-5196
• DOI: 10.3389/neuro.11.008.2008

Modular toolkit for Data Processing (MDP) is a data processing framework written in Python. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. Computations are performed efficiently in terms of speed and memory requirements. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. MDP has been written in the context of theoretical research in neuroscience, but it has been designed to be helpful in any context where trainable data processing algorithms are used. Its simplicity on the user's side, the variety of readily available algorithms, and the reusability of the implemented units make it also a useful educational tool.