The catchiest (and wrong) assertion is this: "even for highly technical aspects like deep learning, fast.ai has shown that people with 1-year of coding experience can become world-class deep learning practitioners" Yes, any Joe can train deep network with dozen lines of Keras. Sure, your startup can use off-the self models and tweak it a bit... That doesn't make you "world-class deep learning practitioner". If you ar…
If you spend one year on applying deep learning, you can train a net on a 100 different data sets. That's where the intuition comes from. You'll debug a lot. People with zero experience with deep learning have ended in the top 10 for Kaggle computer vision competitions. Applied ML does not require a PhD in Computer Science. It is not like you are debugging Cuda as was the case a few years back. Even then, a PhD in st…
Curious if anyone's done this: deep learning on DOM trees, to recognize portions of HTML pages. This has elements in common with both CNNs (where you want surrounding context - parents, ancestors, siblings, and descendants - to influence the recognition of a particular DOM element) and with RNNs (because elements may have an unbounded number of children, and potentially a recurring substructure), but I don't know offhand how you would combine them to solve the problem.
Anyone working on this? A quick literature search turned up nothing.