An example of this might be looking at real estate data and determining which factors lead to higher prices in certain parts of the city. One major manufacturer is using this type of unsupervised ...

In this compendium of articles, learn how the adoption of artificial intelligence (AI) and its integration with ...

The worldwide machine learning market is expected to reach $79.29 billion this year, according to Statista, and grow at a 36 percent CAGR to $503.40 billion by 2030 ...

Imagine having a super-powered lens that uncovers hidden secrets of ultra-thin materials used in our gadgets. Research led by ...

Technological innovations, particularly in the data and machine learning space, are pivotal in addressing the increasing global demand for critical minerals, highlights geoscience software company ...

A new machine learning tool could help fill significant gaps in Canada's public health data, according to research released this week. The program is a machine learning framework that finds ...

10 ways machine learning projects fail AI hallucinations Model bias Legal and ethical risks Poor data quality Model overfitting and underfitting Legacy system integration issues Performance and ...

They compared a range of different machine-learning algorithms, studied their precision and false-positive rates and then used that information to settle on a powerful algorithm. This new algorithm, ...

Equitable machine learning counteracts ancestral bias in precision medicine. Nature Communications, 2025; 16 (1) DOI: 10.1038/s41467-025-57216-8 ...

To bridge this gap, based on their findings, Liu's team used machine learning to analyze how multiple mutations interact to influence treatment outcomes. "Our goal was to find patterns that might ...