A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside ...

Though it might feel great to finish a workout and see "calories burned" pop up on your smartwatch, that number is often surprisingly inaccurate, with estimated error rates of 30%–80%. The watch's ...

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 ...

A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

A one-day short course presented at the American Meteorological Society (AMS) Annual Meeting 2026 106th AMS Annual Meeting - Houston, TX January 25, 2026 at 8:30 AM - 3:45 PM Central Time (Hybrid) ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Experiment tracking is an essential part of modern machine learning workflows. Whether you’re tweaking hyperparameters, monitoring training metrics, or collaborating with colleagues, it’s crucial to ...