Listar por tema "Kafka-ML"
Mostrando ítems 1-7 de 7
-
Distributed federated and incremental learning for electric vehicles model development in Kafka-ML
With the increasing development and deployment of new systems for efficient and clean mobility, Electric Vehicles (EVs) are becoming more and more common among people. Those produce large amounts of data streams that need ... -
Framework para el despliegue flexible de redes neuronales distribuidas en el fog
(2020-11-10)El objetivo general de este Trabajo Fin de Grado ha sido ampliar la funcionalidad de la aplicación Kafka-ML desarrollada por el Grupo de Investigación ERTIS, la cual gestiona y trabaja con redes neuronales. Concretamente, ... -
Functions as a service for distributed deep neural network inference over the cloud-to-things continuum
Bueno Calvente, Altair; Rubio-Muñoz, Bartolomé
; Martín-Fernández, Cristian; Díaz-Rodríguez, Manuel (Wiley, 2024-02-11)
The use of serverless computing has been gaining popularity in recent years as an alternative to traditional Cloud computing. We explore the usability and potential development benefits of three popular open-source serverless ... -
Kafka-ML: Connecting the data stream with ML/AI frameworks
Martín-Fernández, Cristian; Langendoerfer, Peter; Soltani Zarrin, Pouya; Díaz-Rodríguez, Manuel; Rubio-Muñoz, Bartolomé (Elsevier, 2022-01-01)
Machine Learning (ML) and Artificial Intelligence (AI) depend on data sources to train, improve, and make predictions through their algorithms. With the digital revolution and current paradigms like the Internet of Things, ... -
Online learning and continuous model upgrading with data streams through the Kafka-ML framework
Carnero Hijano, Alejandro; Martín-Fernández, Cristian; Jeon, Gwanggil; Díaz-Rodríguez, Manuel (Elsevier, 2024)
A pipeline of constant data streams is being built by the Internet of Things (IoT) to monitor information about the physical environment. In parallel, Artificial Intelligence (AI) is constantly developing and enhancing ... -
The orchestration of Machine Learning frameworks with datastreams and GPU acceleration in Kafka-ML: A deep-learning performance comparative
Machine Learning (ML) applications need large volumes of data to train their modelsso that they can make high-quality predictions. Given digital revolution enablers suchas the Internet of Things (IoT) and the Industry 4.0, ...