Preserving data privacy in Machine Learning pipelines with Federated Learning
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. The performance of ML models heavily relies on their ability to … Read more