I don't think the SKFlow author(s) are at Google. Prettytensor's are, but it isn't Google supported.

I haven't used tflearn or prettytensor, but I have used skflow (and a bit of raw TensorFlow).

SKFlow is nice if you are already using scikit learn because you can drop it straight into your sklean Pipelines[1]. This is great in terms of making it usable alongside other systems.

For example, I currently have a project using an ensemble of regression methods (2 different RandomForest regressors, and 3 XGB methods, then multiple different seeds for each method). SKFlow lets me drop in a TensorFlow regressor as well.

(In actual fact I can't get TF to perform as well as a RF on my featureset, and XGB outperforms it by far. This is using a relatively simple NN though).

[1] http://scikit-learn.org/stable/modules/generated/sklearn.pip...