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The author mentions that one of his goals was to focus on a smaller set of functionality and make it simple and high-performance, but I've got to put a shoutout
by idunning 12y ago
The author mentions that one of his goals was to focus on a smaller set of functionality and make it simple and high-performance, but I've got to put a shoutout to Mocha.jl here [1]. It is essentially Julia's answer to the Caffe deep learning framework (which is linked in the article), and has pure Julia, C++, and CUDA GPU backends. Its under active development but is already pretty amazing. Bonus: it has documentation!
On the contents of this blog post: I really like how the Julia type system is used here. Not only do the types help structure the code and send a signal to the user, but of course there is type-checking to catch errors.
[1]: https://github.com/pluskid/Mocha.jl https://github.com/pluskid/Mocha.jl