Preserving data privacy in Machine Learning pipelines with Federated Learning
FAME's project blog
The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.
Leveraging Large Language Models for Financial Predictions
FAME project blog
In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.
FAME: Federated Decentralized Trusted Data Marketplace for Embedded Finance
IEEE
Due to its multivariate and multipurpose use and reuse, data’s worth is dramatically increasing, leading to an era characterized by the generation of data marketplaces towards accessing, selling, sharing, and trading data and data assets.
Knowledge is power
Article in the newspaper Thinking Cities (Vol V, Mayo 2018): behind the scenes guided tour of Ikaas project
inteGRIDy - Enabling platform for the transformation of Smart Grids
IV Smart Grids Congress, Noviembre 2017
Page 155
Common and open APIs on all platforms
IV Smart Grids Congress, November 2017 - Madrid, Spain
Page 161