
Machine learning algorithms - Liriel
https://github.com/rushter/MLAlgorithms
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eggie5
I think it was a cop-out that he didn't implement the grad function in his
gradient descent routine :(

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coldcode
It would be nice to have a few pointers to descriptions of each algorithm to
understand the concept.

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pyvpx
let's say I wanted to learn the grammar of/how to parse a context-sensitive
grammar from a 100 or thousands of valid examples -- what's the best approach?

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daveguy
First I would suggest you do your own homework assignments. ;)

Currently recurrent neural networks are the best language processing ML
algorithms. Here is a relatively new paper on recurrent neural network
grammars and it references many of the recent papers:

[http://www.aclweb.org/anthology/N16-1024](http://www.aclweb.org/anthology/N16-1024)

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pyvpx
it's not a homework assignment :) thanks for the link. I'm looking to parse a
simple but unknown configuration file format deduced only from known good
examples.

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daveguy
I'm not certain, but to do that optimally I think is an np-complete problem.
If you put some restrictions on it: all files are the same format or only N
fixed formats or context free grammars then it's manageable. Otherwise it
boils down to natural language processing and imperfect, but useful algorithms
in that domain will probably help.

Are you sure it's context sensitive grammar rather than a collection of N
context free grammars? Many file format standards can be expressed as context
free grammars.

If you are trying to figure out something like "what is the unknown XML
structure" based on an example file or files then you are firmly inside
natural language processing.

