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Also, not to mention transfer learning is a big one. Case in point, the silicon valley "not hotdog" classifier which they stopped at hotdog or not due to lack
by deepnotderp 9y ago
Also, not to mention transfer learning is a big one.
Case in point, the silicon valley "not hotdog" classifier which they stopped at hotdog or not due to lack of training data when in reality they could've just used a pre trained net on imagenet. Lol, I was literally cringing through that episode so hard xD
- minimaxir 9y agoThe developer behind the real-world app mentioned why they did not use pretraining, and why you can't always use pretraining: https://news.ycombinator.com/item?id=14347513 https://news.ycombinator.com/item?id=14347513 > We ended up with a custom architecture trained from scratch due to runtime constraints more so than accuracy reasons (the inference runs on phones, so we have to be efficient with CPU + memory), but that model also ended up being the most accurate model we could build in the time we had. (With more time/resources I have no doubt I could have achieved better accuracy with a heavier model!)
- deleted 9y ago[deleted]
- deepnotderp 9y agoYou could still have pre trained the custom architecture.