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Merge pull request #111 from melisgl/master
add Common Lisp and a couple of libraries
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README.md
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README.md
@ -17,6 +17,8 @@ For a list of free machine learning books available for download, go [here](http
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- [General-Purpose Machine Learning](#cpp-general-purpose)
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- [General-Purpose Machine Learning](#cpp-general-purpose)
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- [Natural Language Processing](#cpp-nlp)
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- [Natural Language Processing](#cpp-nlp)
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- [Sequence Analysis](#cpp-sequence)
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- [Sequence Analysis](#cpp-sequence)
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- [Common Lisp](#common-lisp)
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- [General-Purpose Machine Learning](#common-lisp-general-purpose)
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- [Clojure](#clojure)
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- [Clojure](#clojure)
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- [Natural Language Processing](#clojure-nlp)
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- [Natural Language Processing](#clojure-nlp)
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- [General-Purpose Machine Learning](#clojure-general-purpose)
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- [General-Purpose Machine Learning](#clojure-general-purpose)
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@ -142,6 +144,16 @@ For a list of free machine learning books available for download, go [here](http
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#### Sequence Analysis
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#### Sequence Analysis
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* [ToPS](https://github.com/ayoshiaki/tops) - This is an objected-oriented framework that facilitates the integration of probabilistic models for sequences over a user defined alphabet.
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* [ToPS](https://github.com/ayoshiaki/tops) - This is an objected-oriented framework that facilitates the integration of probabilistic models for sequences over a user defined alphabet.
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<a name="common-lisp" />
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## Common Lisp
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<a name="common-lisp-general-purpose" />
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#### General-Purpose Machine Learning
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* [mgl](https://github.com/melisgl/mgl/) - Neural networks (boltzmann machines, feed-forward and recurrent nets), Gaussian Processes
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* [mgl-gpr](https://github.com/melisgl/mgl-gpr/) - Evolutionary algorithms
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* [cl-libsvm](https://github.com/melisgl/cl-libsvm/) - Wrapper for the libsvm support vector machine library
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<a name="clojure" />
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<a name="clojure" />
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## Clojure
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## Clojure
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