원문정보
국제문화기술진흥원
International Journal of Advanced Culture Technology(IJACT)
Volume 6 Number 4
2018.12
pp.303-308
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Demand is increasing rapidly in recent years than supply to machine learning professionals. To alleviate this gap, user-friendly machine learning software that can be used by non-specialists has emerged, which is Machine Learning-as-a-Service(MLaaS). MLaaS provides services that enable businesses to easily leverage ML capabilities without expertise. In this paper, we will compare and analyze features, interfaces, supporting programming language, ML framework, and Machine Learning services of MLaaS, to help companies easily use ML service.
목차
Abstract
1. Introduction
2. Machine Learning-as-a-Service
3. Machine Learning-as-a-Service Providers
3.1 Microsoft Azure Machine Learning Studio
3.2 AWS Machine Learning
3.3 IBM Watson Machine Learning
3.4 Google Cloud Machine Learning Engine
3.5 BigML
4. MLaaS’s Summary Features
5. Conclusion
References
1. Introduction
2. Machine Learning-as-a-Service
3. Machine Learning-as-a-Service Providers
3.1 Microsoft Azure Machine Learning Studio
3.2 AWS Machine Learning
3.3 IBM Watson Machine Learning
3.4 Google Cloud Machine Learning Engine
3.5 BigML
4. MLaaS’s Summary Features
5. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보