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Discussion on: 15.10.19 - This Week Brought to You by the Letter Aurek

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R Sanjabi

The question I think you are asking is does it make sense to have an "aurebesh or not" classifier before doing an aurebesh letter classifier? From a deep learning perspective, I don't think it matters. The two are both straight forward to implement (and harder to generate enough data for) and one doesn't build on the work of the other. A bit like making an "animal or not" classifier doesn't really help with making a "cat or dog" classifier.

It's from week 2 of Practical Deep Learning for Coders (course.fast.ai/videos/?lesson=2). The assignment was basically, here's a bunch of ideas about how to throw stuff together, now go forth and make an image classifier. That level of hands-off is very typical for fast.ai which is in part why I love it so much. The character recognition was my choice. I'm a big Star Wars fan! But also I was looking for images to classify and the data set was already pre-generated. The sample problem that was worked through was "teddy bear, grizzly bear or black bear" other students have done "cricket or baseball". It's a fun project.