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A deep learning model generation method for code reuse and automatic machine learning

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Published:09 October 2018Publication History

ABSTRACT

In recent years, deep neural networks are active in numerous applications such as predictive, advertising and healthcare applications using of image, voice and text recognitions. However, deep neural networks are useful methods but usually require a proper modeling to construct a deep neural network method in any application. Designing a model is a tedious task to be realized in the network, which opens an issue to design an effective software tool for modeling deep neural networks. To get an excellent model for deep neural networks, the developers should have sufficient understanding and experience for deep neural network methods. The developers also require coding skills with the deep learning frameworks and knowledge for the computing resources. This paper presents a software tool based on a Graphical User Interface (GUI) to develop deep neural network models, which train the models with external computing resources and automate the hyper-parameter tuning.

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  1. A deep learning model generation method for code reuse and automatic machine learning

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      • Published in

        cover image ACM Conferences
        RACS '18: Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems
        October 2018
        355 pages
        ISBN:9781450358859
        DOI:10.1145/3264746

        Copyright © 2018 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 9 October 2018

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