Actually, Tensorflow is huge in the data science community, but PyTorch is taking over ML research. TF is last year's cool thing. That's one reason why fast.ai just adopted Pytorch for their courses. Tensorflow is surprisingly low-level and needs libraries like Keras to be used easily. The field of Python ML tools moves fast...

I hope the ML community won't have to suffer the same kind of fatigue syndrom that has plagued the javascript community for the last decade.

Excuse the newbie question but are PyTorch and/or TensorFlow sufficient for developing ML algorithms that can be used directly by a user-facing application? Or is there typically some translation layer involved?

Right, until you don't like something that Google does with Tensorflow in the future or breaks compatibility with your app. I think alternatives in complex abstractions like these are always a good thing. Only a few companies can afford to do it so we have a guarantee that you won't have tens of them. Just a viable alternative.

It's been a while since I played around with tensorflow, how difficult is it to deploy a model as a web service? I'm currently using azure and looking for other options (besides prediction.io).

It's really designed around ease of use. What you're looking for is called TensorFlow Serving.

Cool, thanks for the info.

I'd love to know what sort of ML/AI communities/forums/slacks/discords/whatever communities you participate in, since I'm interesting in joining some.

I don't take Tensorflow seriously anymore... PyTorch is the way to go (gotta try caffe2 at some point).