There's no python vs python3 decision to make. There's no (sane) reason to pick Python 2 in 2018 for new projects.
Conda installer comes with Python prepackaged. So it's really a single exe and one CMD to get a Tensorflow env setup. And, of course, you have access to numpy, pandas, jupyter, PIL ...
Yes, npm installs libraries locally so it avoids the need for something like virtualenv in the first place. Coming from Python, that immediately struck me as a better approach to package management.
You say this, but coremltools (convert from industry standard to Apple's ML framework) initially only supported python 2, so it was annoying to work with some code in Python 2 and some in 3.5.
Conda installer comes with Python prepackaged. So it's really a single exe and one CMD to get a Tensorflow env setup. And, of course, you have access to numpy, pandas, jupyter, PIL ...