amitverma2910 · January 4, 2018 16:18 · Oct 26, 2015 · Oct 26, 2015 · Oct 26, 2015 · Oct 26, 2015
diff --git a/TDA_resources.md b/TDA_resources.md
@@ -1,5 +1,5 @@
 # Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning
-This is just a quick list of resourses on TDA that I through together for [@rickasaurus](https://twitter.com/rickasaurus) after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.
+This is just a quick list of resourses on TDA that I put together for [@rickasaurus](https://twitter.com/rickasaurus) after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.
 
 ## Survey Papers
 Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

diff --git a/TDA_resources.md b/TDA_resources.md
@@ -1,5 +1,5 @@
 # Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning
-This is just a quick list of resourses on TDA that I through together for [@rickasaurus](https://twitter.com/rickasaurus) after he was asking for links to papers, books, etc on Twitter.
+This is just a quick list of resourses on TDA that I through together for [@rickasaurus](https://twitter.com/rickasaurus) after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.
 
 ## Survey Papers
 Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

diff --git a/TDA_resources.md b/TDA_resources.md
@@ -1,4 +1,5 @@
 # Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning
+This is just a quick list of resourses on TDA that I through together for [@rickasaurus](https://twitter.com/rickasaurus) after he was asking for links to papers, books, etc on Twitter.
 
 ## Survey Papers
 Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

diff --git a/TDA_resources.md b/TDA_resources.md
@@ -1,4 +1,4 @@
-# Quick List of Resources for Topological Data Analysis
+# Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning
 
 ## Survey Papers
 Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

diff --git a/TDA_resources.md b/TDA_resources.md
@@ -10,6 +10,7 @@ Both Carlsson's and Ghrist's survey papers offer a very good introduction to the
 * [Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition](https://research.math.osu.edu/tgda/mapperPBG.pdf) A more technical presentation of `Mapper`.
 * [Topological Data Analysis and Machine Learning Theory](https://www.birs.ca/workshops/2012/12w5081/report12w5081.pdf) Applications of TDA to machine learning.
 * Ayasdi, the company founded by Gurjeet Singh and Gunnar Carlsson, has several good [videos and whitepapers](http://www.ayasdi.com/resources) on how they use `Mapper` and TDA in machine learning pipelines.
+* [Applied Algebraic Topology Research Network](https://www.ima.umn.edu/topology/) An online research symposium through the IMA that has several recorded talks dealing with TDA and machine learning.
 
 ## Software
 * [Mapper in Python](http://danifold.net/mapper/)

diff --git a/TDA_resources.md b/TDA_resources.md
@@ -20,4 +20,5 @@ Both Carlsson's and Ghrist's survey papers offer a very good introduction to the
 ## Books
 * [Computational Topology: An Introduction](http://www.amazon.com/Computational-Topology-Introduction-Herbert-Edelsbrunner/dp/0821849255) A good introducgtory book on persistent homology
 * [Elementary Applied Topology](https://www.math.upenn.edu/~ghrist/notes.html) A book by Robert Ghrist that goes beyond applications of algebraic toplogy to data analysis, but is a very good read.  There is a very inexpensive print version and the PDF is available for free.
+* [Topological Signal Processing](http://www.amazon.com/Topological-Signal-Processing-Mathematical-Engineering/dp/364236103X) Not directly related to data analysis, but a good book on using topological methods in signal processing.
 
diff --git a/TDA_resources.md b/TDA_resources.md
@@ -19,5 +19,5 @@ Both Carlsson's and Ghrist's survey papers offer a very good introduction to the
 
 ## Books
 * [Computational Topology: An Introduction](http://www.amazon.com/Computational-Topology-Introduction-Herbert-Edelsbrunner/dp/0821849255) A good introducgtory book on persistent homology
-* [Elementary Applied Topology](https://www.math.upenn.edu/~ghrist/notes.html) A book by Robert Ghrist that goes beyond applications of algebraic toplogy to data analysis, but a very good read.  There is a very inexpensive print version and the PDF is available for free.
+* [Elementary Applied Topology](https://www.math.upenn.edu/~ghrist/notes.html) A book by Robert Ghrist that goes beyond applications of algebraic toplogy to data analysis, but is a very good read.  There is a very inexpensive print version and the PDF is available for free.
 
diff --git a/TDA_resources.md b/TDA_resources.md
@@ -3,15 +3,19 @@
 ## Survey Papers
 Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject
 * [Topology and Data](http://www.ams.org/journals/bull/2009-46-02/S0273-0979-09-01249-X/S0273-0979-09-01249-X.pdf) by Gunnar Carlsson
-* [Barcodes: The Persistent Topology of Data](https://www.math.upenn.edu/~ghrist/preprints/barcodes.pdf)
+* [Barcodes: The Persistent Topology of Data](https://www.math.upenn.edu/~ghrist/preprints/barcodes.pdf) by Robert Ghrist
 
 ## Other Papers and Web Resources
 * [Extracting insights from the shape of complex data using topology](http://www.nature.com/articles/srep01236) A good introductory paper in Nature on the `Mapper` algorithm.
 * [Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition](https://research.math.osu.edu/tgda/mapperPBG.pdf) A more technical presentation of `Mapper`.
 * [Topological Data Analysis and Machine Learning Theory](https://www.birs.ca/workshops/2012/12w5081/report12w5081.pdf) Applications of TDA to machine learning.
-* Ayasdi, the company founded by Gurjeet Singh and Gunnar Carlsson, have several good [videos and whitepapers](http://www.ayasdi.com/resources) on how they use `Mapper` and TDA in machine learning pipelines.
+* Ayasdi, the company founded by Gurjeet Singh and Gunnar Carlsson, has several good [videos and whitepapers](http://www.ayasdi.com/resources) on how they use `Mapper` and TDA in machine learning pipelines.
 
 ## Software
+* [Mapper in Python](http://danifold.net/mapper/)
+* [TDA: Statistical Tools for Topological Data Analysis](https://cran.r-project.org/web/packages/TDA/index.html) R package
+* [JavaPlex](https://github.com/appliedtopology/javaplex) Persistent Homology in Java and Matlab
+* [Perseus](http://www.sas.upenn.edu/~vnanda/perseus/) Persistent Homology in C++
 
 ## Books
 * [Computational Topology: An Introduction](http://www.amazon.com/Computational-Topology-Introduction-Herbert-Edelsbrunner/dp/0821849255) A good introducgtory book on persistent homology

diff --git a/markdown → TDA_resources.md b/markdown → TDA_resources.md
diff --git a/markdown b/markdown
@@ -0,0 +1,19 @@
+# Quick List of Resources for Topological Data Analysis
+
+## Survey Papers
+Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject
+* [Topology and Data](http://www.ams.org/journals/bull/2009-46-02/S0273-0979-09-01249-X/S0273-0979-09-01249-X.pdf) by Gunnar Carlsson
+* [Barcodes: The Persistent Topology of Data](https://www.math.upenn.edu/~ghrist/preprints/barcodes.pdf)
+
+## Other Papers and Web Resources
+* [Extracting insights from the shape of complex data using topology](http://www.nature.com/articles/srep01236) A good introductory paper in Nature on the `Mapper` algorithm.
+* [Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition](https://research.math.osu.edu/tgda/mapperPBG.pdf) A more technical presentation of `Mapper`.
+* [Topological Data Analysis and Machine Learning Theory](https://www.birs.ca/workshops/2012/12w5081/report12w5081.pdf) Applications of TDA to machine learning.
+* Ayasdi, the company founded by Gurjeet Singh and Gunnar Carlsson, have several good [videos and whitepapers](http://www.ayasdi.com/resources) on how they use `Mapper` and TDA in machine learning pipelines.
+
+## Software
+
+## Books
+* [Computational Topology: An Introduction](http://www.amazon.com/Computational-Topology-Introduction-Herbert-Edelsbrunner/dp/0821849255) A good introducgtory book on persistent homology
+* [Elementary Applied Topology](https://www.math.upenn.edu/~ghrist/notes.html) A book by Robert Ghrist that goes beyond applications of algebraic toplogy to data analysis, but a very good read.  There is a very inexpensive print version and the PDF is available for free.
+