--- a/doc/v2_planning/existing_python_ml_libraries.txt	Tue Oct 05 12:26:02 2010 -0400
+++ b/doc/v2_planning/existing_python_ml_libraries.txt	Tue Oct 05 12:31:36 2010 -0400
@@ -96,12 +96,11 @@
 
 3. Recommendations for implementations to wrap
 
-shogun:
-      large scale kernel learning (mostly svms). this wraps other
-libraries we should definitely be interested in, such as libsvm
-(because it is well-established) and others that get state of the art
-performance or are good for extremely large datasets, etc.
-
+* shogun:
+    * large scale kernel learning (mostly svms). this wraps other
+      libraries we should definitely be interested in, such as libsvm
+      (because it is well-established) and others that get state of the art
+      performance or are good for extremely large datasets, etc.
 * milk:
     * k-means
     * svm's with arbitrary python types for kernel arguments