In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.
TotalEnergies' deployment of machine learning at its Port Arthur, Texas, refinery demonstrates how predictive AI can ...
MIT researchers have designed a printable aluminum alloy that’s five times stronger than cast aluminum and holds up at ...
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A urine-based biological aging clock: Machine learning and microRNA offer accurate prediction
Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...
Machine learning models are highly influenced by the data they are trained on in terms of their performance, ...
Vangalapat led the development of a comprehensive MLOps infrastructure at Broadridge, building CI/CD pipelines, automated ...
There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...
The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular ...
A new Israeli study suggests that machine-learning models may soon give growers a far more precise way to predict how much water their crops use each day, while also laying the groundwork for earlier ...
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