Deep Learning Is Easy – Learn Something Harder
I think the article overestimates how much we understand about neural networks, and the novel ways we might use them.<p>Take word2vec for example. It's a two-layer (i.e. not deep) neural network that uses a relatively simple training algorithm. Yet, after 30 minutes it can learn impressive relationships between English words. The method is only 3 years old and businesses continue to find novel ways to apply word2vec. Check out this article:<p><a href="http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-worth-a-thousand-vectors/" rel="nofollow">http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-w...</a><p>They are using word2vec to find clothing items that resemble other products by adding or subtracting descriptors such as "stripes", "blue", or even "pregnant."<p>For my company, we are attempting to normalize medical terminology using word2vec. Here are a couple examples:<p>1. "myocardial" + "infarction" = "MI"<p>2. "ring" + "finger" = "fourth" + "metacarpal"<p>We never would have thought to normalize the names of different body parts, but with word2vec, it does it for us. There's a great deal yet to learn about how this model alone works, let alone deeper networks.