Performance analysis of machine learning libraries

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Published: Sep 30, 2021
DOI: https://doi.org/10.35784/jcsi.2693
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DOI

https://doi.org/10.35784/jcsi.2693

Authors

Ewa Justyna Kędziora

ewa.kedziora@pollub.edu.pl

Grzegorz Krzysztof Maksim

grzegorz.maksim@pollub.edu.pl

Abstract

The paper presents results of performance analysis of machine learning libraries. The research was based on ML.NET and TensorFlow tools. The analysis was based on a comparison of running time of the libraries, during detection of objects on sets of images, using hardware with different parameters. The library, consuming fewer hardware resources, turned out to be TensorFlow. The choice of hardware platform and the possibility of using graphic cores, affecting the increase in computational efficiency, turned out to be not without significance.

Keywords:

machine learning, performance, ML.NET, TensorFlow

References

Article Details

Kędziora, E. J., & Maksim, G. K. (2021). Performance analysis of machine learning libraries. Journal of Computer Sciences Institute, 20, 230–236. https://doi.org/10.35784/jcsi.2693