If you actually need a deep learning model, PyTorch and TensorFlow are both good choices. Topics ... by subclassing keras.Model, but prefers the functional API when possible.

Unlike TensorFlow, PyTorch hasn’t experienced any major ruptures in the core code since the deprecation of the Variable API in version 0.4. (Previously, Variable was required to use autograd ...

Put another way, you write Keras code using Python. The Keras code calls into the TensorFlow library, which does all the work. In Keras terminology, TensorFlow is the called backend engine.

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 (which is Google’s open source machine learning software that now powers applications like Google Translate and many Google Photos features) has now reached a major landmark: its 1.0 ...