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 ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

The TensorFlow.js Node.js environment supports using an installed build of Python/C TensorFlow as a back end, which may in turn use the machine’s available hardware acceleration, for example CUDA.