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.

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

Learning PyTorch deep learning If you’re looking to learn PyTorch, I think your best bet is to work through both the Fast.ai course and one of the more traditional courses at the same time.

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.

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

IBM Research has contributed code to the open-source PyTorch machine learning project that could help to significantly accelerate training.

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 ...

Positive and Unlabeled Learning (PUL) Using PyTorch Dr. James McCaffrey of Microsoft Research provides a code-driven tutorial on PUL problems, which often occur with security or medical data in cases ...

The PyTorch Foundation recently released PyTorch version 2.0, a 100% backward compatible update. The main API contribution of the release is a compile function for deep learning models, which ...