A Machine Learning Gateway for Scientific Workflow Design
Joint Authors
Broll, Brian
Timalsina, Umesh
Völgyesi, Péter
Budavári, Tamás
Lédeczi, Ákos
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-29
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Broll, Brian& Timalsina, Umesh& Völgyesi, Péter& Budavári, Tamás& Lédeczi, Ákos. 2020. A Machine Learning Gateway for Scientific Workflow Design. Scientific Programming،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1209271
Modern Language Association (MLA)
Broll, Brian…[et al.]. A Machine Learning Gateway for Scientific Workflow Design. Scientific Programming No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1209271
American Medical Association (AMA)
Broll, Brian& Timalsina, Umesh& Völgyesi, Péter& Budavári, Tamás& Lédeczi, Ákos. A Machine Learning Gateway for Scientific Workflow Design. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1209271
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1209271
