Delivering Machine Learning Applications via Cloud Platforms: An Experience Report

Cloud technologies enable developers and organizations to focus on their product, without having to consider issues such as local server capacity, infrastructure modifications, data security, licensing or human capital. This paper attempts to explain a case in which a Machine Learning application is...

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Bibliographic Details
Published in:	2020 Turkish National Software Engineering Symposium (UYMS) pp. 1 - 3
Main Authors:	Sener, Yigit, Yetim, Hasan Fahri, Bagriyanik, Selami
Format:	Conference Proceeding
Language:	English
Published:	IEEE 07-10-2020
Subjects:	agility Buildings Cloud computing entrepreneurship Machine learning Maintenance engineering MVP (Minimum Viable Product) PaaS productization Software engineering Web services
Online Access:	Get full text
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Summary:	Cloud technologies enable developers and organizations to focus on their product, without having to consider issues such as local server capacity, infrastructure modifications, data security, licensing or human capital. This paper attempts to explain a case in which a Machine Learning application is deployed via Amazon Web Services (AWS) tools. In doing so, it demonstrates the reasoning behind choosing a cloud-based environment instead of on-premise sources, by putting forward the advantages of the former. On the other hand, it should be noted that the application in this experience is generated with a hybrid approach: It is developed using on-premise infrastructure and then moved to the Cloud environment for the deployment phase only. In this regard, it can be read as a PaaS experience. This study is considered to be a beneficial guide for entrepreneurs and start-ups on a budget who aim at launching their products in a swift and scalable manner.
DOI:	10.1109/UYMS50627.2020.9247050