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 data analysis area is attracting more and more developers and researchers, but the solutions developed need to be modularized into well-defined components in order to be able to parallelize some stages and obtain a good performance in the execution stage. 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 multi-label classification of images to recommend tourist attractions and validates the use of serverless to serve models of Machine Learning.