In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

a.The architecture of the all-optical CNN for OAM-mediated machine learning, which can be applied to encode a data-specific image into OAM states. The photonic neural network comprises a trainable ...

Driverless AI really is able to create and train good machine learning models without requiring machine learning expertise from users. Machine learning, and especially deep learning, have turned out ...

Tesla has been granted a patent for a system that uses image data captured by a vehicle’s camera to predict a three-dimensional trajectory of a machine learning feature. The trained machine learning ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

In this special guest feature, Henrik Skogström, Head of Growth at Valohai, discusses how MLOps (machine learning operations) is becoming increasingly relevant as it is the next step in scaling and ...

Our eLibrary offers over 25,000 IMF publications in multiple formats. This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML ...