figured out good way to handle footnotes/references

bfortuner · Apr 23, 2017 · 77b1da9 · 77b1da9
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diff --git a/docs/activation_functions.rst b/docs/activation_functions.rst
@@ -1,12 +1,10 @@
 .. _activation_functions:
 
 ====================
-Activation functions
+Activation Functions
 ====================
 
-.. toctree::
-  :maxdepth: 1
-  :titlesonly:
+.. contents:: :local:
 
 ELU
 ===
@@ -95,3 +93,8 @@ Tanh
 ====
 
 Be the first to contribute!
+
+
+.. rubric:: References
+
+.. [1] Example
diff --git a/docs/backpropagation.rst b/docs/backpropagation.rst
@@ -4,6 +4,8 @@
 Backpropagation
 ===============
 
+.. contents:: :local:
+
 The goals of backpropagation are straightforward: adjust each weight in the network in proportion to how much it contributes to overall error. If we iteratively reduce each weight's error, eventually we’ll have a series of weights the produce good predictions.
 
 
@@ -179,5 +181,4 @@ Code example
 
 .. rubric:: References
 
-- Reference1
-
+.. [1] Example
diff --git a/docs/calculus.rst b/docs/calculus.rst
@@ -4,7 +4,7 @@
 Calculus
 ========
 
-Brief overview of derivatives, gradients and the chain rule.
+.. contents:: :local:
 
 .. _derivative:
 
@@ -279,7 +279,7 @@ There are two additional properties of gradients that are especially useful in d
 
 .. _chain_rule:
 
-Chain Rule
+Chain rule
 ==========
 
 The chain rule is a formula for calculating the derivatives of composite functions. Composite functions are functions composed of functions inside other function(s).
@@ -418,35 +418,16 @@ We then input the derivatives and simplify the expression:
   \end{align}
 
 
-.. rubric:: References
-
-.. [#] `Khan Academy Derivatives Introduction <https://www.khanacademy.org/math/multivariable-calculus/multivariable-derivatives/partial-derivative-and-gradient-articles/a/directional-derivative-introduction>`_
-
-  * https://en.wikipedia.org/wiki/Derivative
-
-  * https://en.wikipedia.org/wiki/Partial_derivative
-
-  * https://en.wikipedia.org/wiki/Gradient
-
-  * https://betterexplained.com/articles/vector-calculus-understanding-the-gradient/ Understanding
-
-  * https://www.khanacademy.org/math/multivariable-calculus/multivariable-derivatives/partial-derivative-and-gradient-articles/a/the-gradient
-
-  * https://www.khanacademy.org/math/multivariable-calculus/multivariable-derivatives/gradient-and-directional-derivatives/v/gradient-and-contour-maps
 
-  * https://www.mathsisfun.com/calculus/derivatives-introduction.html
-
-  * http://tutorial.math.lamar.edu/Classes/CalcI/DefnOfDerivative.aspx
-
-  * http://www.algebrahelp.com/lessons/simplifying/foilmethod/pg2.htm
-
-  * http://www.sosmath.com/calculus/diff/der00/der00.html
-
-  * http://csrgxtu.github.io/2015/03/20/Writing-Mathematic-Fomulars-in-Markdown/
-
-  * https://en.wikipedia.org/wiki/Chain_rule#Higher_dimensions
-
-  * https://www.khanacademy.org/math/calculus-home/taking-derivatives-calc/chain-rule-calc/v/chain-rule-introduction
+.. rubric:: References
 
-  * http://tutorial.math.lamar.edu/Classes/CalcI/ChainRule.aspx
+.. [1] https://en.wikipedia.org/wiki/Derivative
+.. [2] https://www.khanacademy.org/math/multivariable-calculus/multivariable-derivatives/partial-derivative-and-gradient-articles/a/directional-derivative-introduction
+.. [3] https://en.wikipedia.org/wiki/Partial_derivative
+.. [4] https://en.wikipedia.org/wiki/Gradient
+.. [5] https://betterexplained.com/articles/vector-calculus-understanding-the-gradient
+.. [6] https://www.mathsisfun.com/calculus/derivatives-introduction.html
+.. [7] http://tutorial.math.lamar.edu/Classes/CalcI/DefnOfDerivative.aspx
+.. [8] https://www.khanacademy.org/math/calculus-home/taking-derivatives-calc/chain-rule-calc/v/chain-rule-introduction
+.. [9] http://tutorial.math.lamar.edu/Classes/CalcI/ChainRule.aspx
 
diff --git a/docs/cnn.rst b/docs/cnn.rst
@@ -4,8 +4,10 @@
 CNNs
 ====
 
+.. contents:: :local:
+
 Intro to CNNs
 
-.. toctree::
-  :maxdepth: 2
+.. rubric:: References
 
+.. [1] Example
diff --git a/docs/contribute.rst b/docs/contribute.rst
@@ -0,0 +1,7 @@
+.. _contribute:
+
+==========
+Contribute
+==========
+
+Become a contributor! Check out our `github <http://github.com/bfortuner/ml-cheatsheet/>`_ for more information.
diff --git a/docs/forwardpropagation.rst b/docs/forwardpropagation.rst
@@ -4,6 +4,11 @@
 Forwardpropagation
 ==================
 
+.. contents:: :local:
+
+Overview
+========
+
 .. image:: images/neural_network_simple.png
     :align: center
 
@@ -33,7 +38,8 @@ Let’s write a method feed_forward() to propagate input data through our simple
 
 ..    :pyobject: MyClass   #Target a specific class.function in a file
 
+
 .. rubric:: References
 
-- Reference1
+.. [1] Example
 
diff --git a/docs/gan.rst b/docs/gan.rst
@@ -4,9 +4,11 @@
 GANs
 ====
 
-Intro to Generative Adversarial Networks
+.. contents:: :local:
+
 
-.. toctree::
-  :maxdepth: 2
+Intro to Generative Adversarial Networks
 
+.. rubric:: References
 
+.. [1] Example