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.

PyTorch is an open-source machine learning library developed by Facebook’s AI Research lab (FAIR). It’s known for its flexibility, ease of use, and as a powerful tool for deep learning ...

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 ...

Originally created by Meta, PyTorch has become an important tool for machine learning and people developing AI models.

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

Learn how to install PyTorch open-source machine learning library in Windows &enhance your deep learning for AI & machine learning projects.

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

Both PyTorch and TensorFlow support deep learning and transfer learning. Transfer learning, which is sometimes called custom machine learning, starts with a pre-trained neural network model and ...

But why should you choose to use PyTorch instead of other frameworks like MXNet, Chainer, or TensorFlow? Let’s look into five reasons that add up to a strong case for PyTorch.