I'm going to make a big claim:
Libraries like sklearn (#python), caret (#rstats) and MLJ (#julialang)
are never going have great APIs for working with models like deep neural networks, or any other kind of model, where the hyper-parameters are nontrivial functions. And that is Ok
-
Show this thread
-
-
Replying to @algo_luca
The obvious solution is to allow the passing in of a function object (lambda) for parameters like neural architecture. In Python and R this is no go. Since they need to hit a C backend that doesn't want to do a slow call back into python/R. Some hope for other languages here.
1 reply 0 retweets 0 likes
Replying to @oxinabox_frames
Here I stand with you: it's a technological problem.
MLJ, given that it's written in #julialang, could bring some cool innovations to the table, API-wise.
There is some movement in @rustlang land as well, but we are quite far from a working prototype.
7:36 AM - 19 May 2019
0 replies
0 retweets
1 like
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.
Writing about stuff to learn how it works, mostly in Rust.
Lead Engineer at