A machine-learning algorithm demonstrated the capability ... "Our implementation simply breaks down the big data into smaller units that can be processed with the available resources.

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve ...

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...

The first available use case for BeeKeeper, Mount Sinai and Morehouse is for chronic heart failure (CHF). AI model developers ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

BLKB, CFLT and CME are revolutionizing Big Data with AI-powered tools, transforming industries from finance to social media.

Manufacturing execution systems (MES) generate mountains of data. Deciphering the data, however, often consumes hours daily.

The investing world has a significant problem when it comes to data about small and medium-sized enterprises (SMEs). This has nothing to do with data quality or accuracy — it’s the lack of any data at ...

and a Jupyter notebook lab/Peer Review to implement the PCA algorithm. This week, we are working with clustering, one of the most popular unsupervised learning methods. Last week, we used PCA to find ...

Combining this information with current and historical satellite data, they trained a machine-learning algorithm to assess ... "Ten meters by ten meters is a big square. When sunlight falls ...