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I created this talk for the Enterprise Big Data track of O'Reilly's Strata conference - so it's not a technical description of how deep learning works. Rather,
by jph00 14y ago
I created this talk for the Enterprise Big Data track of O'Reilly's Strata conference - so it's not a technical description of how deep learning works. Rather, it's an attempt to show why it's important, and how it fits into current data science trends.
The "Biggest Data Science Breakthrough of the Decade" in the title is a rather bold claim, I know... But I think it might be justified. If there are are bigger breakthroughs, I'd be interested in people's thoughts about what they might be.
- pyre 14y agoIf by "of the Decade," you mean 2010-2020, then you've still got another 7 years to be proven right/wrong.
- spikels 14y agoNot sure which decade you are talking about. If you mean the 2010s or the next 10 years we'll just have to see what the next 7 or 10 years bring. But if you mean the past 10 years I would have to say that the "distributed storage and processing" revolution (Hadoop and others) has had a much bigger impact on data science than all of neural networks including deep networks. Why the need to hype what is already a well publicized development? I'm starting to cringe whenever I hear "data science" or "big data" and I love this stuff.