作者
Rustem Dautov, Erik Johannes Husom, Fotis Gonidis, Spyridon Papatzelos, Nikolaos Malamas
发表日期
2022/10/10
研讨会论文
2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
页码范围
363-368
出版商
IEEE
简介
The role of Machine Learning (ML) engineers in mobile development has become increasingly important in recent years, as more and more business-critical mobile applications depend on AI components. Many development teams already include dedicated ML engineers who aim to follow agile development practices in their work, as part of the larger MLOps concept. However, the availability of MLOps tools tailored specifically towards mobile platforms is scarce, often due the limited support for non-native programming languages such as Python, as well as the unsuitability of native programming languages such as Java and Kotlin to support ML-related programming tasks. This paper aims to address this gap and describes a plug-in architecture for developing, deploying and running data ingestion and processing components written in Python on the Android platform. With the possibility to pass a user-defined …
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R Dautov, EJ Husom, F Gonidis, S Papatzelos… - 2022 18th International Conference on Wireless and …, 2022