Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

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) ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

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.

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

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 ...

Ask Calvin graduates about their education and one word seems synonymous: formative. If you look at the institution’s foundational documents, it’s not hard to figure out why. From the Expanded ...

Scientists at the University of Nottingham have discovered how specific surface patterns on plastics used for medical devices can drastically reduce the ability of bacteria to attach and multiply, ...

Google Colab is a really handy tool for anyone working with machine learning and data stuff. It’s free, it runs in the cloud, and it lets you use Python without a lot of fuss. Whether you’re just ...

Neuroscientists at the Sainsbury Wellcome Centre (SWC) at UCL have discovered that the brain uses a dual system for learning through trial and error. This is the ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...