Minor edits to docs.

Change: 150258994

tensorflow/docs_src/about/index.md

@@ -3,10 +3,10 @@
 This section provides a few documents about TensorFlow itself,
 including the following:
 
-  * @{roadmap$Roadmap}, which summarizes upcoming additions to TensorFlow.
-  * @{uses$TensorFlow in Use}, which provides a link to our model zoo and
+  * @{$roadmap$Roadmap}, which summarizes upcoming additions to TensorFlow.
+  * @{$uses$TensorFlow in Use}, which provides a link to our model zoo and
     lists some popular ways that TensorFlow is being used.
   * @{$bib$TensorFlow White Papers}, which provides abstracts of white papers
     about TensorFlow.
-  * @{attribution$Attribution}, which specifies how to attribute and refer
+  * @{$attribution$Attribution}, which specifies how to attribute and refer
     to TensorFlow.

tensorflow/docs_src/community/index.md

@@ -2,11 +2,11 @@
 
 This section contains the following documents:
 
-  * @{welcome$Welcome to the TensorFlow Community}, which explains how
+  * @{$welcome$Welcome to the TensorFlow Community}, which explains how
     you can get involved, where to report issues, and where to join
     like-minded TensorFlow enthusiasts online.
   * @{$documentation$Writing TensorFlow Documentation}, which explains
     TensorFlow's documentation conventions.  If you are modifying
     TensorFlow source code or documentation, please read this guide.
-  * @{style_guide$TensorFlow Style Guide}, which identifies coding style
+  * @{$style_guide$TensorFlow Style Guide}, which identifies coding style
     conventions that TensorFlow developers and users should follow.

tensorflow/docs_src/deploy/index.md

@@ -5,11 +5,11 @@ the following documents:
 
   * @{$distributed$Distributed TensorFlow}, which explains how to create
     a cluster of TensorFlow servers.
-  * @{tfserve$TensorFlow Serving}, which describes TensorFlow Serving--an
+  * @{$tfserve$TensorFlow Serving}, which describes TensorFlow Serving--an
     open-source serving system for machine learning models. This document
     provides a short introduction to TensorFlow Serving; the bulk of the
     documentation about TensorFlow Serving is in a
     [separate website](https://tensorflow.github.io/serving/serving_basic).
-  * @{hadoop$How to run TensorFlow on Hadoop}, which has a highly
+  * @{$hadoop$How to run TensorFlow on Hadoop}, which has a highly
     self-explanatory title.
 

tensorflow/docs_src/extend/index.md

@@ -14,7 +14,7 @@ TensorFlow:
     add support for your own shared or distributed filesystem.
   * @{$new_data_formats$Custom Data Readers}, which details how to add support
     for your own file and record formats.
-  * @{estimators$Creating Estimators in tf.contrib.learn}, which explains how
+  * @{$estimators$Creating Estimators in tf.contrib.learn}, which explains how
     to write your own custom Estimator.  For example, you could build your
     own Estimator to implement some variation on standard linear regression.
 

tensorflow/docs_src/get_started/index.md

@@ -3,7 +3,7 @@
 For a brief overview of TensorFlow programming fundamentals, see the following
 guide:
 
-  * @{$getting_started/get_started$Getting Started with TensorFlow}
+  * @{$get_started/get_started$Getting Started with TensorFlow}
 
 MNIST has become the canonical dataset for trying out a new machine learning
 toolkit.  We offer three guides that each demonstrate a different approach
@@ -14,7 +14,7 @@ to training an MNIST model on TensorFlow:
   * @{$mnist/pros$Deep MNIST for Experts}, which is more-in depth than 
     "MNIST for ML Beginners," and assumes some familiarity with machine 
     learning concepts.
-  * @{$tutorials/mnist$TensorFlow Mechanics 101}, which introduces MNIST through
+  * @{$mnist/mechanics$TensorFlow Mechanics 101}, which introduces MNIST through
     the low-level API.
 
 For developers new to TensorFlow, the high-level API is a good place to start. 

tensorflow/docs_src/install/install_mac.md

@@ -45,7 +45,7 @@ the specified versions. If upgrading is not possible, you may still run
 TensorFlow with GPU support, but only if you do both of the following:
 
   * Install TensorFlow from sources as described
-    @{install_sources$here}.
+    @{$install_sources$here}.
   * Install or upgrade to at least the following NVIDIA versions:
     * CUDA toolkit 7.0 or greater
     * cuDNN v3 or greater