In machine learning in production there are 2 phases: training and inference (usage)
In training we have spark docker images where you can run cuda right from spark submit.
In inference mode we sit on top of DC/OS by mesosphere embedding lightbend's (they created scala) micrsoservices technology conductr to scale out automatically on a mesos based cluster: http://www.slideshare.net/agibsonccc/deep-learning-in-produc...
Here is more on our enterprise distribution SKIL: http://www.slideshare.net/agibsonccc/skil-dl4j-in-the-wild-m...
If you're curious where the talent is, I cowrote the flagship oreilly book on deeplearning: http://shop.oreilly.com/product/0636920035343.do
We also employ deep learning phds doing everything from deep learning research in health care, ex nvidia, ex cloudera among others.
In machine learning in production there are 2 phases: training and inference (usage)
In training we have spark docker images where you can run cuda right from spark submit.
In inference mode we sit on top of DC/OS by mesosphere embedding lightbend's (they created scala) micrsoservices technology conductr to scale out automatically on a mesos based cluster: http://www.slideshare.net/agibsonccc/deep-learning-in-produc...
Here is more on our enterprise distribution SKIL: http://www.slideshare.net/agibsonccc/skil-dl4j-in-the-wild-m...
If you're curious where the talent is, I cowrote the flagship oreilly book on deeplearning: http://shop.oreilly.com/product/0636920035343.do
We also employ deep learning phds doing everything from deep learning research in health care, ex nvidia, ex cloudera among others.