Analyze Performance of Embedded Systems with Machine Learning Algorithms
Künye
Ersoy M., Şansal U. (2021) Analyze Performance of Embedded Systems with Machine Learning Algorithms. In: Hemanth J., Yigit T., Patrut B., Angelopoulou A. (eds) Trends in Data Engineering Methods for Intelligent Systems. ICAIAME 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-79357-9_23Özet
This article aims to analyze the performance of embedded systems using various machine learning algorithms on embedded systems. For this, data set were analyzed using Python programming language and related libraries. Using different machine learning algorithms, it has been useful in terms of giving us an idea about how these cards are sufficient for solving deep learning and artificial intelligence problems or how close they will be to the desired performances. Raspberry pi and jatson nano embedded system boards were used for performance measurement and they were compared with notebook performance.
