{"title":"通过云平台交付机器学习应用:一份经验报告","authors":"Yigit Sener, Hasan Fahri Yetim, Selami Bagriyanik","doi":"10.1109/UYMS50627.2020.9247050","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":358654,"journal":{"name":"2020 Turkish National Software Engineering Symposium (UYMS)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Delivering Machine Learning Applications via Cloud Platforms: An Experience Report\",\"authors\":\"Yigit Sener, Hasan Fahri Yetim, Selami Bagriyanik\",\"doi\":\"10.1109/UYMS50627.2020.9247050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":358654,\"journal\":{\"name\":\"2020 Turkish National Software Engineering Symposium (UYMS)\",\"volume\":\"176 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Turkish National Software Engineering Symposium (UYMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UYMS50627.2020.9247050\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Turkish National Software Engineering Symposium (UYMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UYMS50627.2020.9247050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 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.