Everyone's into deep learning, but what would I actually do with it? With some other field, like computer graphics, one can fairly quickly get a 3D cube spinning on their screen and know it has some relation to the special effects in the Star Wars movie they just saw. No one makes it obvious what the hobbyist can expect to do with deep learning or how it relates to the broader world.
I don't know. I'm not even into deep learning but I still see things all the time I wish I could test deep learning on.
Everyones into Graphics programming, but what would I actually do with it? The uses are myriad, you can build Star Wars Movies, you can build computer games. You can do CAD and 3D modelling and printing, you can visualize fluid simulations But each is an entire field. The same with Deep Learning - You can do image classification for medical diagnosis. Self Driving Cars. Realtime Translation. OCR. You can model chemic…
One of my partner's tasks as a legal assistant is to go through mountains of OCRed PDFs and classify them and extract pieces of data so that lawyers and paralegals can go through them more easily. Do you imagine deep learning would be an appropriate means of automating that, or is it overkill?
Not overkill at all, but youy should know that there are a lot of competitors in the e-discovery software category, and they do a lot besides classification, starting from the ingestion of email archives, through extraction of attachments (recursively, because Outlook PSTs get mailed as attachments too), identifying and attributing quoted text, deduplication of messages and documents, SNA, clustering, normalization, canonicalization, NER, synonym identification (aside from correctly identifying people referred to by nicknames, advanced implementations can also figure out when people are using a code-word to evade filters), etc.
I didn't see k-means nearest neighbor in the list. Also, wouldn't a mathematical statistics be a prerequisite?
As far as I can tell, Deep learning in practice is pretty far ahead of the theory, so people are largely following their intuition around rather than being guided by theory.
Everyone's into deep learning, but what would I actually do with it? With some other field, like computer graphics, one can fairly quickly get a 3D cube spinning on their screen and know it has some relation to the special effects in the Star Wars movie they just saw. No one makes it obvious what the hobbyist can expect to do with deep learning or how it relates to the broader world.
deep learning is where databases where 20 years ago.
you can easily imagine putting data in a db like server, and querying that data asking things about that model in respect to other things at your disposal in different times.