Title of article
A Machine Learning Gateway for Scientific Workflow Design
Author/Authors
Broll, Brian Institute for Software Integrated Systems and Department of Electrical Engineering and Computer Science - Vanderbilt University, Nashville, TN, USA , Timalsina, Umesh Institute for Software Integrated Systems and Department of Electrical Engineering and Computer Science - Vanderbilt University, Nashville, TN, USA , Volgyesi, Pe´ter Institute for Software Integrated Systems and Department of Electrical Engineering and Computer Science - Vanderbilt University, Nashville, TN, USA , Budava´ri, Tama´s 2 Department of Applied Mathematics and Statistics - Department of Physics and Astronomy, and Department of Computer Science - Johns Hopkins University, Baltimore, MD, USA , deczi, A´ kos Le´ Institute for Software Integrated Systems and Department of Electrical Engineering and Computer Science - Vanderbilt University, Nashville, TN, USA
Pages
15
From page
1
To page
15
Abstract
The paper introduces DeepForge, a gateway to deep learning for scientific computing. DeepForge provides an easy to use, yet powerful visual/textual interface to facilitate the rapid development of deep learning models by novices as well as experts. Utilizing a cloud-based infrastructure, built-in version control, and multiuser collaboration support, DeepForge promotes reproducibility and ease of access and enables remote execution of machine learning pipelines. The tool currently supports TensorFlow/Keras, but its extensible architecture enables easy integration of additional platforms.
Keywords
Machine Learning , Gateway , Workflow Design , Scientific
Journal title
Scientific Programming
Serial Year
2020
Full Text URL
Record number
2610317
Link To Document