This view seems incomplete and problematic:
The strong advantage of TensorFlow is it flexibility is designing highly modular model which also can be a disadvantage too for beginners since lots of the pieces must be considered together for creating the model. This issue has been facilitated as well by developing high-level APIs such as Keras and Slim which gather lots of the design puzzle pieces. The interesting point about TensorFlow is that its trace can be found anywhere these days.
I'm feeling TF is getting left behind compared to PyTorch. Dynamic graphs is a powerful thing. It's also kind of sad Keras is not yet supporting PyTorch.
Are all those animated gifs are absolutely necessary there? What kind of purpose do they serve?
Can anyone precisely describe TensorFlow in a single sentence?
Wow thank you for sharing! One of my resolutions for the year 2018 is to build something with TensorFlow.