Microservice Based Architecture for Data Classification
Distributed Systems, Services, Microservices, Architecture, Docker, Machine Learning, Deep Learning, Transfer Learning
Smart solutions for data classification data that make use of Deep Learning are in a moment of ascension. The area of data analysis is attracting more and more developers and researchers, but the solutions developed need to be in a scalable and modularized environment to be delivered to a large number of users. From this motivation, this work presents a generic architecture for data classification, named Machine Learning in Microservices Architecture (MLMA), that can be reproduced in a production environment. In addition, the use of the architecture is presented in a project that makes a multi-label classification of images to recommend tourist attractions and an architecture mapping in a text analysis project is introduced.