incubator-systemml git commit: [MINOR] Remove redundant links from docs index

[de...@apache.org]

Repository: incubator-systemml
Updated Branches:
  refs/heads/master 14830a241 -> 1ebe2e178


[MINOR] Remove redundant links from docs index

Remove redundant links from docs index.
Remove 'Coming Soon' from PyDML Language Reference.
Replace Caffe2DML absolute reference with relative reference.


Project: http://git-wip-us.apache.org/repos/asf/incubator-systemml/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-systemml/commit/1ebe2e17
Tree: http://git-wip-us.apache.org/repos/asf/incubator-systemml/tree/1ebe2e17
Diff: http://git-wip-us.apache.org/repos/asf/incubator-systemml/diff/1ebe2e17

Branch: refs/heads/master
Commit: 1ebe2e17809174334c001e6b308dfb760dc91657
Parents: 14830a2
Author: Deron Eriksson <de...@us.ibm.com>
Authored: Thu May 18 23:46:13 2017 -0700
Committer: Deron Eriksson <de...@us.ibm.com>
Committed: Thu May 18 23:46:13 2017 -0700

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 docs/index.md | 9 ++-------
 1 file changed, 2 insertions(+), 7 deletions(-)
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http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/1ebe2e17/docs/index.md
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diff --git a/docs/index.md b/docs/index.md
index 96b834d..e10d48d 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -45,23 +45,18 @@ for running SystemML from Spark via Scala, Python, or Java.
   * [Spark Shell Example (Scala)](spark-mlcontext-programming-guide#spark-shell-example)
   * [Jupyter Notebook Example (PySpark)](spark-mlcontext-programming-guide#jupyter-pyspark-notebook-example---poisson-nonnegative-matrix-factorization)
 * [Spark Batch](spark-batch-mode) - Algorithms are automatically optimized to run across Spark clusters.
-  * See [Invoking SystemML in Spark Batch Mode](spark-batch-mode) for detailed information.
 * [Hadoop Batch](hadoop-batch-mode) - Algorithms are automatically optimized when distributed across Hadoop clusters.
-  * See [Invoking SystemML in Hadoop Batch Mode](hadoop-batch-mode) for detailed information.
 * [Standalone](standalone-guide) - Standalone mode allows data scientists to rapidly prototype algorithms on a single
 machine in R-like and Python-like declarative languages.
-  * The [Standalone Guide](standalone-guide) provides examples of algorithm execution
-  in Standalone Mode.
 * [JMLC](jmlc) - Java Machine Learning Connector.
-  * See [Java Machine Learning Connector (JMLC)](jmlc) for more information.
-* *Experimental* [Caffe2DML API](http://apache.github.io/incubator-systemml/beginners-guide-caffe2dml) for Deep Learning.
+* *Experimental* [Caffe2DML API](beginners-guide-caffe2dml) for Deep Learning.
 
 ## Language Guides
 
 * [Python API Reference](python-reference) - API Reference Guide for Python users.
 * [DML Language Reference](dml-language-reference) -
 DML is a high-level R-like declarative language for machine learning.
-* **PyDML Language Reference** **(Coming Soon)** -
+* **PyDML Language Reference** -
 PyDML is a high-level Python-like declarative language for machine learning.
 * [Beginner's Guide to DML and PyDML](beginners-guide-to-dml-and-pydml) -
 An introduction to the basics of DML and PyDML.