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Scientific scripting in Java with JShellLab and application to deep learning using DeepLearning4j.

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Bibliographic Details
Title: Scientific scripting in Java with JShellLab and application to deep learning using DeepLearning4j.
Authors: Papadimitriou, Stergios
Source: International Journal of Modeling, Simulation & Scientific Computing; Aug2020, Vol. 11 Issue 4, pN.PAG-N.PAG, 15p
Subject Terms: VIRTUAL reality, CONVOLUTIONAL neural networks, SCRIPTS, APPLICATION program interfaces, DEEP learning
Abstract: JShellLab is an easy to use MATLAB-like environment for the Java Virtual Machine (JVM). It implements scientific scripting based on the JShell Application Programming Interface (API) of modern Java. The paper illustrates that JShellLab can significantly facilitate and simplify the development of complex computational demanding scientific software at the JVM. The novelty at the JShellLab is that it completely hides the complexity and the intricate dependencies of optimized scientific software. As an example, the demanded field of deep learning is exploited. Specifically, the implementation of effective practical deep learning-based systems using the JShellLab environment and the Deeplearning4j Java library is considered. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Modeling, Simulation & Scientific Computing is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
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