I think my favorite part of this is that inevitably people will write type definitions for TensorFlow.js in TypeScript, Flow, ReasonML, Purescript, and more.
It has always seemed like data science and machine learning tasks have always been most popular in dynamic languages like Python, Julia, and R. I really hope this can be a bridge over to typed machine learning APIs!
(Of course, I’m also interested to hear about your favorite typed machine learning library if you have some that you already use)
Absolutely spot on... I love watching Siraj Raval's videos on ML - but darn it every other video has a 2 or 3 minute segment where he's just scratching his head - finally to realize there is a typo that could have been caught with a typed language!
I would love to see some full Tensor Flow bindings for Go. It's concurrency system is great for data science tasks. The statically linked binary makes it great for distributed workflows.
I think dynamic languages are a bad fit, because they force the programmer to think in data-flow graphs, whereas a more static language could allow for more offloading of complexity to a compiler (i.e. let the compiler build the data-flow graph, which is essentially what we've been doing for decades).
It has always seemed like data science and machine learning tasks have always been most popular in dynamic languages like Python, Julia, and R. I really hope this can be a bridge over to typed machine learning APIs!
(Of course, I’m also interested to hear about your favorite typed machine learning library if you have some that you already use)