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[Discussion] using data parallelism + distributed computing for faster/scalable ML/DL
I've read dozens of articles and journals outlining the theororetical benfits of solving scalability, cost, training time problems in ML/DL using distributed computing. I would like to discuss with this sub the utility of building a platform that does just that.
Ive been in software dev for about 10 years, and have been a lurking ML fanboy for the past 2. I'm looking to get my teeth into a significant project, solving real world problems in this space. I'll outline my idea: please feel free to comment any thoughts, feedback, …!-->