and here, by Github stars. Not included above because it seems far less reliable as a usage metric.pic.twitter.com/ZSaAOaNiAQ
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poor torch. Apart from not having access to the python ecosystem. It's very nice dl lib
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congrats!
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Missing
@h2oai's#DeepLearning by@ArnoCandel. https://github.com/h2oai/h2o-3 400 forks, 1000+ stars. More info: http://docs.h2o.ai/h2o/latest-stable/h2o-docs/booklets/DeepLearningBooklet.pdf … -
okay, but it doesn't have an issues page, which makes it harder to evaluate. Why?
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yes, we can call TensorFlow from Sparkling Water (distributed, on Spark), so anything is possible
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CNTK in all four top tens I see RT
@fchollet: The Deep Learning frameworks landscape, May 2016.pic.twitter.com/2TxXkZqPk7
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metric idea - github issues closed?
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where did you grab this data from? who should i give reference to if i use it somewhere? ;)
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it is scraped it from Github. I wrote a script that just generates the tables, on demand.
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