Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

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

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

Empromptu's "golden pipeline" approach tackles the last-mile data problem in agentic AI by integrating normalization directly into the application workflow — replacing weeks of manual data prep with ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...

Artificial intelligence (AI) systems are now widely used by millions of people worldwide, as tools to source information or ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...