orhankislal commented on a change in pull request #406: user docs for 
madlib-keras deep learning
URL: https://github.com/apache/madlib/pull/406#discussion_r291613169
 
 

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 File path: src/ports/postgres/modules/deep_learning/madlib_keras.sql_in
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 @@ -28,6 +28,1355 @@
 
 m4_include(`SQLCommon.m4')
 
+/**
+@addtogroup grp_keras
+
+<div class="toc"><b>Contents</b><ul>
+<li class="level1"><a href="#keras_fit">Fit</a></li>
+<li class="level1"><a href="#keras_evaluate">Evaluate</a></li>
+<li class="level1"><a href="#keras_predict">Predict</a></li>
+<li class="level1"><a href="#example">Examples</a></li>
+<li class="level1"><a href="#notes">Notes</a></li>
+<li class="level1"><a href="#background">Technical Background</a></li>
+<li class="level1"><a href="#literature">Literature</a></li>
+<li class="level1"><a href="#related">Related Topics</a></li>
+</ul></div>
+
+\warning <em> This MADlib method is still in early stage development.
+Interface and implementation are subject to change. </em>
+
+This module allows you to use SQL to call deep learning
+models designed in Keras [1], which is a high-level neural
+network API written in Python.
+Keras was developed for fast experimentation.  It can run
+on top of different backends and the one that is currently
+supported by MADlib is TensorFlow [2].  The implementation
+in MADlib is distributed and designed to train
+a single large model across multiple segments (workers)
+in a Greenplum database.
 
 Review comment:
   This might sound like we only support gpdb, we should mention postgres as 
well.

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