So should I start searching for android(if yes, then a little more discussion on it would be great) or focus on the repository for now?
I've read mlpack's and boost's necessary documentation​, and currently running tests. On Mar 16, 2017 1:40 AM, "Shoaib Zafar" <[email protected]> wrote: > I also had this idea and gave it a thought before 😀. Theoretically, > mlpack libraries can be seamlessly used in android studio using android > ndk. > > Guys at tensorflow have achieved it (i guess the whole library is not > fully working but classification works​. It can act as a reference point). > I've also read that Snapdragon is working on optimizing tensorflow in their > upcoming processor(Snapdragon 835?) which mlpack might be able benefit from > in the future! > > And Marcus, I've skimmed through the projects ideas, "Essential Deep > Learning modules" caught my attention mostly. Reinforced learning also > seemed interesting(I am more interested in implementation of algorithms) > but this Android idea is great! > Thanks! > > > On Mar 16, 2017 12:57 AM, "Ryan Curtin" <[email protected]> wrote: > > On Wed, Mar 15, 2017 at 05:02:24PM +0100, Marcus Edel wrote: > > Hello Shoaib, > > > > welcome and thanks for getting in touch! > > > > > A little overview of my background, I am a CS major student in my 3rd > year. I > > > have also taken AI's course (which was majority focused on machine > learning, and > > > involved implementing algorithms). I've been also exploring online > courses > > > (coursera and udacity). Apart from this, I have been closely dealing > and > > > observing open source community at xda-developers(Link to profile). > > > > Maybe it's time to bring mlpack on android :) Also, I heard really good > things > > about the coursera and udacity courses. > > I think a very long time ago James Cline had mlpack programs running on > his phone. I know that mlpack compiles fine on ARM (I have an ARM > Chromebook I sometimes work from) so it should definitely still be > possible. I guess, it could be an exciting application to train a > neural network on a desktop, serialize it, and then load it on a phone > to do local classification directly on the phone. > > -- > Ryan Curtin | "This is how Number One works!" > [email protected] | - Number One > > >
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