Efficient and versatile data analytics for deep networks
Dario García-Gasulla, Jonathan Moreno-Vázquez, Javier A. Espinosa-Oviedo, José M. Conejero, Genoveva Vargas‐Solar, Rosa M. Badia, Ulises Cortés, Toyotaro Suzumura · UPCommons institutional repository (Universitat Politècnica de Catalunya) · 2015
Deep networks (DN) perform cognitive tasks related with image and text at human-level. To extract and exploit the knowledge coded within these networks we propose a framework which combines state-of-the-art technology in parallelization, storage and analysis. Our goal, to make DN models available to all data scientists.