Well, certainly. It’s not like TensorFlow has stood still for all that time. TensorFlow 1.x was all about building static graphs in a very un-Python manner, but with the TensorFlow 2.x line, you ...

The people behind TensorFlow soon took note of this, and adopted many of PyTorch’s most popular features in TensorFlow 2.0. A good rule of thumb is that you can do anything that PyTorch does in ...

Is PyTorch better than TensorFlow for general use cases? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world ...

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 ...

PyTorch defaults to eager execution mode, meaning that its API calls execute when invoked, rather than being added to a graph to be run later. TensorFlow has since improved its support for eager ...

Graphs: One of the reasons for TensorFlow’s popularity is its graph-based architecture. All operations in TensorFlow are depicted and executed inside a graph, which helps define how data is ...

Maker of the popular PyTorch-Transformers model library, Hugging Face today said it’s bringing its NLP library to the TensorFlow machine learning framework. The PyTorch version of the library ...