Machine Learning in Construction: Predicting Oil Temperature Anomalies in a Tunnel Boring Machine

Today, we continue our series of blog posts highlighting presentations from the 2nd Edition of Seville Machine Learning School (MLSEV). You may read the first post about the ‘6 Challenges of Machine Learning’ here. One of the very interesting real-world use case presentations during the event was that of Guillem Ràfales from SENER. Founded in […]

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