Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data.

Researchers have determined how to build reliable machine learning models that can understand complex equations in real-world situations while using far less training data than is normally expected.

Azure Machine Learning interoperates with popular open source tools, such as PyTorch, TensorFlow, Scikit-learn, Git, and the MLflow platform to manage the machine learning lifecycle.

Cloudian’s new PyTorch connector is built on Nvidia Corp.’s GPUDirect Storage technology and optimized for Nvidia Spectrum-X ...

Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties even with limited ...