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 ...

In 2026, artificial intelligence skills sit on the short list for promotions in analytics, product, and operations. Teams want people who can frame the right problem, choose workable models, and ...

AI's coding capabilities prompt students to reevaluate the value of traditional computer science education and future career paths.

A new 3D-printed aluminum alloy is stronger than traditional aluminum, due to a key recipe that, when printed, produces aluminum (illustrated in brown) with nanometer scale precipitates (in light blue ...

Objective: To construct a prediction model for teicoplanin (TEIC) plasma concentrations through machine learning and deep learning techniques in patients with liver disease using real-world clinical ...

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.

School of Artificial Intelligence and Data Science, Unversity of Science and Technology of China, Hefei 230026, P. R. China Suzhou Institute for Advanced Research, University of Science and Technology ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

In the seamless fusion of artificial intelligence and mechanical engineering, MIT students are carving a new frontier for design innovation. Faez Ahmed, MIT's Doherty Chair in Ocean Utilization and ...

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 ...

Wave enables rapid prototyping of new optimization ideas and algorithms through its high-level abstractions and symbolic programming model. Kernel authors can quickly express complex tensor operations ...