Sergey Korolev libfun

## concurrent_iterator.py
import multiprocessing

def __process__(q_in, q_out):
    np.random.seed()
    while True:
        data = q_in.get()
        if data is None:
            break
        q_out.put((preprocess(data[0]), data[1]))


## NIPS2016.md

      
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    Note: I'm updating this gist as I encounter new reviews, so make sure you're reading the latest revision!
Just as the previous year I collected (and keep doing so) links to various summaries and takeaways from this year's NIPS.

NIPS 2016 Symposium on People and machines: Public views on machine learning, and what this means for machine learning researchers. (Notes and panel discussion) by /u/gcr
NIPS 2016 summary, wrap up, and links to slides by /u/beamsearch
Post NIPS Reflections by Neil Lawrence
[Some general take aways from #NIPS2016](https://medium.com/@IgorCarron/some-general-take-aways-from-ni
	import multiprocessing

	def __process__(q_in, q_out):
	np.random.seed()
	while True:
	data = q_in.get()
	if data is None:
	break
	q_out.put((preprocess(data[0]), data[1]))