Using PyTorch to streamline machine-learning projects A platform that lets surgeons browse videos of past operations has found a way to make its machine learning more effective.

OpenAI announced that it will adopt Facebook's PyTorch machine learning development framework in the near future, eschewing Google's TensorFlow.

The open-source PyTorch project is widely used for machine learning (ML) training. Its anticipated 2.0 version is now generally available.

PyTorch’s dependency chain—additional packages that are downloaded during its installation—includes a library called torchtriton that was hosted on PyTorch’s own index for nightly builds.

Soumith Chintala from Facebook AI Research, PyTorch project lead, talks about the thinking behind its creation, and the design and usability choices made. Facebook is now unifying machine learning ...

A positive and unlabeled learning (PUL) problem occurs when a machine learning set of training data has only a few positive labeled items and many unlabeled items. PUL problems often occur with ...