I'm presenting on Strongly Typed Deep Learning with #haskell in a few weeks to the #StLouis machine learning and data science meetup.
I wish that #haskell's #tensorflow story was a bit better. I see a lot of potential for some really great capabilities to emerge from the combo of a language great for DSLs and with a lot of correctness guarantees, but the current solutions seem to require too much #categorytheory for a gentle intro to non-haskellers
Any suggestions for ways to make it easier?
@cercerilla maybe ask https://gitter.im/dataHaskell/Lobby ? haskell-tensorflow could definitely do with some more examples and tutorials (that do something more interesting than linear regression!). The sad part is that most regular TF tutorials require things like tf.contrib which is only available in Python, so not easy to "port" tutorials.
