Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

Abstract: Matrix multiplication is a crucial operation in many data-intensive workloads. Given the large size of matrices in today's workloads, it is common to split the computation into tasks ...

In this tutorial, we will discover how to harness the power of an advanced AI Agent, augmented with both Python execution and result-validation capabilities, to tackle complex computational tasks. By ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Google DeepMind’s AI systems have taken big scientific strides in recent years — from predicting the 3D structures of almost every known protein in the universe to forecasting weather more accurately ...

Python libraries are pre-written collections of code designed to simplify programming by providing ready-made functions for specific tasks. They eliminate the need to write repetitive code and cover ...

Abstract: Large-scale matrix multiplication is a critical operation in various fields such as machine learning, scientific computing, and graphics processing, but performing it on a single machine ...

This article is adapted from an edition of our Off the Charts newsletter originally published in October 2021. Off the Charts is a weekly, subscriber-only guide to The Economist’s award-winning data ...

Spicing up Algebra I class isn’t easy, and getting students to check their answers can be especially challenging. However, introducing short Python programs to check answers is easy and fun, and your ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.