3 ms·
While I agree that you could build a demo in Deep Learning 101 that could work for some small set of examples, I disagree that this is 101 level material. Face
by sarthakjain 10y ago
While I agree that you could build a demo in Deep Learning 101 that could work for some small set of examples, I disagree that this is 101 level material.
Facebook just released: https://techcrunch.com/2017/02/02/facebooks-ai-unlocks-the-ability-to-search-photos-by-whats-in-them/ https://techcrunch.com/2017/02/02/facebooks-ai-unlocks-the-a...
You could also call this Deep Learning 101. But it really isn't because building a usable platform that works at scale actually delivers performance and solves problems is a lot tougher than what can be taught in an intro to Deep Learning 101 course.
- ChaitanyaSai 10y agoJust poked around a bit with your API, and the learning with just 25 samples is impressive! And the getting training samples from the web is a great touch. But that 25 sample number seems too low for classes that are "closer" together? How do you quantify if you have done a good job on training or if you need some varied samples?
- sarthakjain 10y agoThanks for trying us out! Internally we have validation metrics which have a number that says how good a model is at class separation. One naive way to do this entropy (-plogp). We are planning on exposing this to users soon. So once you create a model you'll receive feedback as to how "good" we think it is. In case it's not working well we might ask you for more data (we hope we don't need to do this too frequently)