45 lines
1.5 KiB
Markdown
45 lines
1.5 KiB
Markdown
# random optimization code
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not unlike [my dsp repo,](https://github.com/notwa/dsp)
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it's also a bunch of half-baked python code that's kinda handy.
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i give no guarantee anything provided here is correct.
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don't expect commits, docs, or comments to be any verbose.
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### heads up
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this was formerly a gist.
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**i might rewrite the git history**
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at some point to add meaningful commit messages.
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## other stuff
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if you're coming here from Google: sorry, keep searching.
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i know Google sometimes likes to give random repositories a high search ranking.
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maybe consider one of the following:
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* [keras](https://github.com/fchollet/keras)
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for easy tensor-optimized networks.
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strong [tensorflow](http://tensorflow.org) integration as of version 2.0.
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also check out the
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[keras-contrib](https://github.com/farizrahman4u/keras-contrib)
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library for more components based on recent papers.
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* [theano's source code](https://github.com/Theano/theano/blob/master/theano/tensor/nnet/nnet.py)
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contains pure numpy test methods to reference against.
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* [minpy](https://github.com/dmlc/minpy)
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for tensor-powered numpy routines and automatic differentiation.
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* [autograd](https://github.com/HIPS/autograd)
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for automatic differentiation without tensors.
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## dependencies
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python 3.5+
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numpy scipy h5py sklearn dotmap
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## contributing
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i'm just throwing this code out there,
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so i don't actually expect anyone to contribute,
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*but* if you do find a blatant issue,
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maybe [yell at me on twitter.](https://twitter.com/antiformant)
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