"For now, relatively few people are versed in the tricks needed to get deep learning to work well"
How does one exactly become one of these people? Is any of this information public yet?
How does one exactly become one of these people? Is any of this information public yet?
There's a lot of other knowledge/expertise/intuition that's required to make working implementations. There have been some deep learning tutorials at recent conferences that might be more in-depth. (See my previous comment [1] for details.)
Another good way to learn is to look at some open source implementations, such as caffe from berkeley [2] or overfeat from NYU [3].
In addition to showing how to choose architectures or set params, they also have tricks for speeding things up. This is actually very important, as they can make orders of magnitude difference (training in hours vs days).
[1] https://news.ycombinator.com/item?id=7742192
Most Machine Learning research that is not done by top secret labs is available publicly. Start looking at papers by Geoffrey Hinton. Could also take a look at word2vec if you are into NLP.
Most of the academic/industry papers are available. Just browse the nips/icml/sigir/etc conference websites.
But then you'll need to apply that knowledge - ideally by working in the industry. Or you can go try your luck in kaggle and other competitions.