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You're seeing hate for deep learning on HN!?! I'd love to see something approaching critical thought! Most of the comments I see are silly fluff about the singu

by irq11 9y ago

You're seeing hate for deep learning on HN!?! I'd love to see something approaching critical thought! Most of the comments I see are silly fluff about the singularity and/or AGI and killer robots. But seriously: I think you're overstating the case. I've enjoyed watching the fast.ai videos, and I think deep learning is a clear choice for some areas right now. Many others, no. If you're working in a data-limited domain, in particular (i.e. most of them) there are probably better first choices. I know plenty of folks who have used deep learning to achieve no better than comparable results to the simpler methods they were using before. But yes, the initial engineering costs of a deep learning system have come down a lot further than I thought before I watched your videos.

marze 9y ago
It is world changing tech. If skeptical, wait and see.
minimaxir 9y ago
> You're seeing hate for deep learning on HN!?! Most of the hate for deep learning on HN is usually against using it in titles as clickbait. (i.e. just simply taking a pretrained/predefined model and changing the source dataset without any optimization) The in-depth explanations of mechanics discussed in deep learning as noted in fast.ai courses and this submission do justify the use of the deep learning moniker, though.
deepnotderp 9y ago
A pre trained deep net can work very well in a data limited domain if there's sufficient overlap.
- irq11 9y ago
  Yes, but that's true of any ML approach. Deep learning is great if you're dealing with a hugely dimensional problem, and you have the data to train the model. If one of those things is not true (and usually, one of those things is not true), you're better off starting simple.
  - jacquesm 9y ago
    That's an excellent point and one that kept me from trying the deep learning approach for a long time. But in the end the machine + rudimentary deep learning provided its own dataset and that really made it work. So even if I didn't have the data to train the model I had enough data to bootstrap the process and sometimes that's all you need.
    - irq11 9y ago
      Yes, agreed. Your use case was interesting to me in the way that you bootstrapped the problem. If only more domains were like that!

by irq11 9y ago

marze 9y ago

It is world changing tech. If skeptical, wait and see.

minimaxir 9y ago

> You're seeing hate for deep learning on HN!?! Most of the hate for deep learning on HN is usually against using it in titles as clickbait. (i.e. just simply taking a pretrained/predefined model and changing the source dataset without any optimization) The in-depth explanations of mechanics discussed in deep learning as noted in fast.ai courses and this submission do justify the use of the deep learning moniker, though.

deepnotderp 9y ago

A pre trained deep net can work very well in a data limited domain if there's sufficient overlap.

irq11 9y ago
Yes, but that's true of any ML approach. Deep learning is great if you're dealing with a hugely dimensional problem, and you have the data to train the model. If one of those things is not true (and usually, one of those things is not true), you're better off starting simple.
- jacquesm 9y ago
  That's an excellent point and one that kept me from trying the deep learning approach for a long time. But in the end the machine + rudimentary deep learning provided its own dataset and that really made it work. So even if I didn't have the data to train the model I had enough data to bootstrap the process and sometimes that's all you need.
  - irq11 9y ago
    Yes, agreed. Your use case was interesting to me in the way that you bootstrapped the problem. If only more domains were like that!