Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

One example involved a system built by a summer intern for his own project work. The tool geolocates devices within a drawing set and links them to a digital twin of the facility. Instead of searching ...

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

Explore how machine learning in insurance enhances risk assessment, fraud detection, and personalization. ✓ Subscribe for ...

Abstract: This study uses an AI-enhanced cybersecurity events dataset to utilize the effectiveness of leveraging machine learning algorithms Logistic Regression, Decision Tree, and Random Forest for ...

Machine learning is helping neuroscientists organize vast quantities of cells’ genetic data in the latest neurobiological cartography effort.

Abstract: Q-learning and double Q-learning are well-known sample-based, off-policy reinforcement learning algorithms. However, Q-learning suffers from overestimation bias, while double Q-learning ...

From the Department of Bizarre Anomalies: Microsoft has suppressed an unexplained anomaly on its network that was routing traffic destined to example.com—a domain reserved for testing purposes—to a ...

“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...

Their findings demonstrate that although spurious correlations—a simple example of which is when a machine-learning system, not having "seen" many cows pictured at the beach, classifies a photo of a ...