the more Pythonic approach offered by PyTorch’s automatic differentiation (autograd) seems to have won the war against static graphs. Unlike TensorFlow, PyTorch hasn’t experienced any major ...

In case you’re curious how TensorFlow’s graph execution works, it allows for optimizing computations and provides a clear overview of operations and dependencies. On the other side ...

TensorFlow, which competes with frameworks such as PyTorch and Apache MXNet ... and gain introspection into TensorFlow apps. Each graph operation can be evaluated and modified separately and ...

PyTorch is still growing, while TensorFlow’s growth has stalled. Graph from StackOverflow trends. StackOverflow traffic for TensorFlow might not be declining at a rapid speed, but it’s ...

This article will discuss the seven popular tools and frameworks used for developing AI applications: TensorFlow, PyTorch, Keras, Caffe, Microsoft Cognitive Toolkit, Theano and Apache MXNet.

The catalog has a collection of models based on popular frameworks such as Tensorflow, PyTorch, Keras, XGBoost and Scikit-learn. Each of the models is packaged in a format that can be deployed in ...