Biggest change for me is it seems like there's more of an incentive to use tf.keras instead of external Keras, for simplicity.
I wonder what's the underlying issue behind this disparity. Wonder if it the teams themselves behind those products...
Tensorflow is not necessarily the most loved framework, despite it being in python, and being around for years now. This is in stark contrast to the way TF was marketed and hyped up, as the f/w that's going to take over the world of DL. That clearly didn't happen.
I think torch/pytorch is more popular (but don't quote me on that). And there are about half-a-dozen more competing with these two.
Putting two and two together, Angular and TF likely have more similarities than differences when it comes to community response.
Surely it's just the difference between a product for mass consumption and a niche one.
It will be interesting to see if tensorflow retains a fairly high level of popularity over time. The 1->2 transition is a big risk for them because so many people are on TF 1, there's a ton of intrusive changes.
