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Deep usually means more than one hidden layer. The basic algorithms are similar to back propagation, being based on gradient descent, but there are a lot of tri
by noelwelsh 12y ago
Deep usually means more than one hidden layer. The basic algorithms are similar to back propagation, being based on gradient descent, but there are a lot of tricks (or refinements, depending on your point-of-view) to make the learning more robust and efficient.
Deep learning is a specific area within machine learning.
- sgt101 12y agoI tried training a 4 layer network in as a young man (because, why not) a day later, no convergence, some calculations revealed that an expectation of many 1000's of days (I have a memory of 1 million, but that could be bs) before the network would converge. So "deep" networks have been around for many decades, and they haven't, because you couldn't train them. Now we have computers that are 10,000* faster (at least) and training algorithms that are much faster too these architectures are interesting.
- noelwelsh 12y agoThis comment nails it. I think it is under-appreciated how much machine learning progress is enabled by increasing computing power. This is not to deny algorithmic improvements, but it's hard to refine algorithms if you can't actually run them.
- lohengramm 12y agoThank you all above for the explanations.