[mslate]

We used it for a sales email classification problem--it significantly out-performed our conventional approaches (i.e. logistic regression + bag-of-words), but we were not PhDs and none of our job titles were "data scientist" so I guess that makes us charlatans ;)

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.

[amrrs]

Wondering what Tensorflow has to do with that out-performance since it must be all about the model/algorithm that you implemented in that - like you could've had a TF code running the same conventional approach you mentioned above - which wouldn't have done any magic. Isn't it the algorithm like a convnet doing the magic rather than TF itself responsible for it?

[mslate]

Yes, TF is merely a framework implementing convolutional neural nets, not a novel implementation of them.

We chose TF over other convolutional neural net libraries because it was 1. Python and 2. heavily sponsored by Google.

[brucephillips]

What TF model did you use?

[mslate]

This was "ages" ago, pre 1.0 so ~2 years ago. TBH, I can't recall which model we used. We ran it in production for several months on a proprietary training dataset of 30k emails, re-training it once a week.

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?"