add link to github

Author: Simon Lefrancois

doc/index.txt

@@ -25,7 +25,9 @@ training them on a GPU.
 The algorithm tutorials have some prerequisites.  You should know some python,
 and be familiar with numpy. Since this tutorial is about using Theano, you
 should read over the `Theano basic tutorial`_ first.  Once you've done that,
-read through our :ref:`gettingstarted` chapter -- it introduces the notation, and [downloadable] datasets used in the algorithm tutorials, and the way we do optimization by stochastic gradient descent.  
+read through our :ref:`gettingstarted` chapter -- it introduces the notation, and downloadable datasets used in the algorithm tutorials, and the way we do optimization by stochastic gradient descent.
+
+The code is available on the `Deep Learning Tutorial repositories <https://github.com/lisa-lab/DeepLearningTutorials>`_.
 
 The purely supervised learning algorithms are meant to be read in order:
 

doc/rnnrbm.txt

@@ -17,7 +17,7 @@ Modeling and generating sequences of polyphonic music with the RNN-RBM
   The script also assumes that the content of the `Nottingham Database of folk tunes <http://www.iro.umontreal.ca/~lisa/deep/data/Nottingham.zip>`_ has been extracted in the ``../data`` directory.
   Alternative MIDI datasets are available `here <http://www-etud.iro.umontreal.ca/~boulanni/icml2012>`_.
 
-  Note that both dependencies above can be setup automatically by running the ``download.sh`` script in the ``../data`` directory.
+  Note that both dependencies above can be setup automatically by running the `download.sh <https://github.com/lisa-lab/DeepLearningTutorials/blob/master/data/download.sh>`_ script in the ``../data`` directory of the `Deep Learning Tutorials repository <https://github.com/lisa-lab/DeepLearningTutorials>`_.
 
 .. caution::
   Need Theano 0.6 or more recent.