Are you ready to take your smart solutions to the next level? During this session, you will learn how to integrate AI and ML platforms for analysis and processing of digital twin data in systems based on FIWARE. In this session, we’ll cover all aspects of ML Ops, including how to deploy ML in edge systems, and show you how to use AI and ML to turn data into actionable insights and business value.
You’ll discover how to leverage the power of AI and ML to optimize your smart solutions and gain a competitive edge. You’ll learn how to implement ML Ops in solutions powered by FIWARE, enabling you to easily deploy machine learning models and update them in real-time. We’ll also discuss how to deploy ML in edge systems, allowing you to process data locally and avoid the latency of sending it to a central server.
This session will invite participants to discover how to put data to work and turn it into wisdom that drives business value. Moreover, different experiences on how to automatize ML, especially regarding training and deploying ML models into solutions powered by FIWARE in different real scenarios.
If you are interested in learning how to turn machine learning models towards perfection and deliver ML solutions more easily as part of solutions powered by FIWARE, to extract the most out of data, this session is for you.
Presentations:
ML-OPS for the continuum edge-cloud – Joaquin Salvachua, Associate Professor, University Polytechnic of Madrid
Publishing and monetizing AI/ML-based services in data spaces – Juanjo Hierro, CTO, FIWARE Foundation
TinyML: Machine Learning in the edge with FIWARE components – José Andrés Muñoz Arcentales, Assistant Professor, University Polytechnic of Madrid
The need of effective data flows for Machine Learning and Deep Learning; from Structure, Learning to Performance on Applications – Miguel Gonzalez-Mendoza, Research Professor, Tecnologico de Monterrey