Many developers who use Python for machine learning are now switching to PyTorch. Find out why and what the future could hold for TensorFlow.

Is PyTorch better than TensorFlow for general use cases? This question was originally answered on Quora by Roman Trusov.

Which of these deep learning frameworks should you use? In this article, we’ll take a high-level comparative look at TensorFlow, PyTorch, and JAX.

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 ...

This PyTorch vs TensorFlow guide will provide more insight into both but each offers a powerful platform for designing and deploying machine learning models.

As Spisak told me, one of the most important new features in PyTorch 1.1 is support for TensorBoard, Google’s visualization tool for TensorFlow that helps developers evaluate and inspect models.

As the popularity of the Python programming language persists, a user survey of search topics identifies a growing focus on AI and machine learning tasks and, with them, greater adoption of related ...

The latest version of Facebook's open source deep learning library PyTorch comes with quantization, named tensors, and Google Cloud TPU support.

TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet are the seven most popular frameworks for developing AI applications.

Facebook wants to make sure the open-source PyTorch machine-learning framework supports the needs of developers who want to use its AI models in production systems, not just research projects, it ...