Merge pull request #17 from MITx/vik/deployment_work

Update readme and add license

Readme.md

-Project to integrate machine learning based essay scoring with xserver. Aspell must be installed and added to path to run.  numpy, scipy, sklearn, and nltk also need to be installed.
+ML
+====================
 
-Nltk also requires the treebank maxent tagger and wordnet to be installed.  These can be installed through the nltk downloader(nltk.download()), or programatically through  `python -m nltk.downloader maxent_treebank_pos_tagger wordnet` .
+Overview
+---------------------
+This is a repo with functions that can score arbitrary free text and numeric predictors.
+This is licensed under the AGPL, please see LICENSE.txt for details.
+The goal here is to provide a high-performance, scalable solution that can predict targets from arbitrary values.
 
-Runnable files:
+Note that this is a library.  You will need to implement your own code to make it runnable.  The ml-service-api repo in
+the edX github organization is an API wrapper for this code.  See http://github.com/edx/ml-service-api for more information.
 
-1. tests/test_models.py 
+How to Contribute
+-----------------------
+Contributions are very welcome.  The easiest way is to fork this repo, and then make a pull request from your fork.
 
-	Generates test models when used like: `python create_test_models.py train_file prompt_file model_path`.  Use `python create_test_models.py train.tsv prompt.txt models/essay_set_1.p` to generate a model using sample data.
+The current backlog is in the issues section. Please feel free to open new issues or work on existing ones.
 
-2. test_server_code/pyxserver_wsgi.py
-
-	Starts a server instance that can be sent answers to score.  Calls grade.py to score responses.  Run server with `gunicorn -w 4 -b 127.0.0.1:3031 pyxserver_wsgi:application` . 
-
-3. tests/test.py
-
-	Submits test data found in directories within the tests folder to the xserver and displays results.  See tests/simple_essay for an example of how to format files.  You need payload.json, wrong.txt, and answer.txt to make a test.
-
-Testing:
-
-Tests can be run by running nosetests in the tests directory.  Make sure the test server is running first! 
+Detailed Information
+-------------------------
+Please look in the docs folder for more detailed documentation.  There is a README there that explains how to build
+and view the docs.
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