Neural Networks Are Impressively Good at Compression
People are knocking this guy for not being an expert and maybe getting some details wrong. Maybe it's a little bit like watching a non-programmer stumble their way through a blog post about learning to program- experienced programmers may cringe a bit.<p>But I really appreciate these kinds of write-ups: he declares his non-expertise up-front, and then proceeds to document his understanding as he goes along. There's something useful about this kind of blog post for non-experts.<p>I'm working my way through Karpathy's writeup on RNNs (<a href="http://karpathy.github.io/2015/05/21/rnn-effectiveness" rel="nofollow">http://karpathy.github.io/2015/05/21/rnn-effectiveness</a>). I've mechanically translated his Python to Go, and even managed to make it work. But I <i>still</i> don't entirely understand the math behind it. Now obviously Karpathy IS an expert, but despite his extremely well-written blog post, a lot of it is still somewhat impenetrable to me ("gradient descent"? I took Linear Algebra oh, about 25 years ago). So sometimes it's nice to see
other people who are a bit bewildered by things like tanh(), yet still press on and try to understand the overall process.<p>And FWIW I had the same reaction as the author when I started toying around with neural nets- it's shocking how small the hidden layer can be and still do useful stuff. It seems like magic, and sometimes you have to run through it step-by-step to understand it.