Name
Title | ||
|---|---|---|
Implementing a Microservices Architecture for Predicting the Opinion of Twitter Users on COVID Vaccines. |
Abstract | ||
|---|---|---|
A strong trend in the software industry is to merge the activities of deployment and operationalization through the DevOps approach, which in the case of artificial intelligence is called Machine Learning Operations (MLOps). We present here a microservices architecture containing the whole pipeline (frontend, backend, data predictions) hosted in Docker containers which exposes a model implemented for opinion prediction in Twitter on the COVID vaccines. This is the first description in the literature of implementing a microservice architecture using TorchServe, a library for serving Pytorch models. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.3233/SHTI220417 | Medical Informatics Europe (MIE) |
Keywords | DocType | Volume |
Artificial Intelligence,COVID-19,MLOps,Social Media,Vaccines | Conference | 294 |
ISSN | Citations | PageRank |
1879-8365 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guillaume Guerdoux | 1 | 0 | 0.68 |
| Bissan Audeh | 2 | 0 | 0.34 |
| Théophile Tiffet | 3 | 0 | 0.68 |
| Cédric Bousquet | 4 | 0 | 0.68 |