Mid-career workers are facing real anxiety about AI. Tackling that by upskilling has been a painful but rewarding process, says Liang Kaixin.

Abstract: Linear systems involved in engineering and scientific calculations can be more easily analyzed using similarity transformation. However, understanding the numerous abstract linear algebra ...

This year has seen some amazing advancements in fundamental mathematics. Researchers have made breakthroughs in geometry, topology, chaos theory, and more. And a startling three of our top 10 ...

The New York State Education Department is pushing new math guidelines, including a recommendation that teachers stop giving timed quizzes — because it stresses students out. The new guidelines also ...

nvmath-python brings the power of the NVIDIA math libraries to the Python ecosystem. The package aims to provide intuitive pythonic APIs giving users full access to all features offered by NVIDIA's ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

Getting input from users is one of the first skills every Python programmer learns. Whether you’re building a console app, validating numeric data, or collecting values in a GUI, Python’s input() ...

Whether you’re solving geometry problems, handling scientific computations, or processing data arrays, calculating square roots in Python is a fundamental task. Python offers multiple approaches for ...

Alabama was the only state to earn a "Strong" rating its math education in a new report from the National Council on Teacher Quality released Tuesday. The state, which has historically leaned red, ...

Recent advancements in LLMs such as OpenAI-o1, DeepSeek-R1, and Kimi-1.5 have significantly improved their performance on complex mathematical reasoning tasks. Reinforcement Learning with Verifiable ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...