Understand how Intersection over Union (IoU) works and how to implement it using PyTorch. This metric is essential for ...

In the early days of PyTorch, you had to write completely custom code for data loading. Now however, the vast majority of PyTorch systems I've seen (and created myself) use the PyTorch Dataset and ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Following new best practices, Dr. James McCaffrey of Microsoft Research revisits multi-class classification for when the variable to predict has three or more possible values. This is the second of ...

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.

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

AstraZeneca is using PyTorch-powered algorithms to discover new drugs The pharmaceutical firm has revealed how it is using sophisticated machine-learning tools to speed up drug discovery.

Google Cloud also said it is supporting open source implementations of deep learning models to foster greater use of PyTorch/XLA, including ResNet-50 and the Deep Learning Recommendation Model.

TensorFlow also lost steam in the research community, which started preferring the flexibility PyTorch offered a few years ago, resulting in a decline in the use of TensorFlow in research papers.

Schroepfer noted that PyTorch isn’t actually any faster than the Caffe 2 AI framework, rather the advantage is that it’s just much easier to use.