Despite the AI hype, tools are proving valuable for leading-edge chip manufacturing. More aggressive feature scaling and ...

The natural protein universe is vast, and yet, going beyond and designing new proteins not observed in nature can yield new ...

Advancements in biomedical technologies have significantly facilitated the diagnosis and monitoring of diseases. Nonetheless, traditional diagnostic ...

Mass spectrometry is critical in drug discovery — but legacy systems, data silos, and poor metadata are slowing progress. This white paper, in partnership with Thermo Fisher, shares how experts from ...

What began as a Ph.D. project has grown into a website with 120,000 unique visitors each year. With the platform OpenML, researcher Jan van Rijn is contributing to open science, aiming to make machine ...

In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels—essential for AI to operate independently in everyday settings—closed-source ...

Researchers from Okinawa Institute of Science and Technology outline a strategy for using machine learning (ML) to address ...

In today's data-driven world, data literacy is becoming a crucial skill across all industries. Employers are increasingly ...

Early-warning signs of marsh decline provided by the model could be crucial for conservation. “Once [marsh] loss occurs, that ...

At the forefront of discovery, where cutting-edge scientific questions are tackled, we often don't have much data. Conversely ...

Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data transformations.D ...