Data Management in Deep Learning Practice and Infrastructure

 The Full Stack Deep Learning course is great, because it really dives into the nuts and bolts of the details associated with the actual practice of deep learning.  This lecture on data management infrastructure is a good example.  

This lecture is worth the price of admission (which is basically just the time required to watch it) just for the section 41 minutes in that contrasts a Hadoop Cluster vs just using unix command line tools to implement a particular part of a deep learning data management stack.  Once again proving the time honored KISS (keep i simple stupid) principal that seems to be an alternate acronym for Occam's Razor (the simplest solution is probably the best, and certainly the most desirable unless you are billing by the hour, then by all means use that complex solution).


Observations

1:  Being much more of a signal processing and algorithms guy, i was not really familiar with a lot of what was covered in this lecture. So i learned a lot of useful information about how to construct cloud based systems.  

2:  We were pushing HDF5 here last year in a HTC post, so the fact that we shouldn't be anymore was useful information for sure.

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