> It’s really bad to use. There’s so much hype around it, but the number of people who are actually using it to build real things that make a difference is probably very low.
I wonder how many data scientists out there are actually developing Tensorflow models for a mission-critical project at work. I'm not. I have used Tensorflow successfully within my personal projects, but I've yet to need it for anything "real."
That service offering among the rest of the business was marginal so it never became an offering that our sales team pitched our customers very aggressively, so in this particular case TensorFlow did not push the needle so-to-speak.
I regret not following through more on that project, but hey, you've only got so much political capital to burn when people ask you "and how does it make us money?"
We chose TF over other convolutional neural net libraries because it was 1. Python and 2. heavily sponsored by Google.
It is probably quite far from a standard usage, but Tensorflow may be used to write some custom graphical models inference, for example. To be practical these algorithms can not be implemented in, say, pure python.
The point is Tensorflow gets you pretty close to assembly level computation. The alternative is to write in, say, cython - which is much more time consuming to write, and does not give you parallelization for free. Another alternative I guess would be torch, but that is the same as tensorflow the way I see it.