Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/17996#discussion_r117545657
--- Diff: docs/ml-guide.md ---
@@ -66,41 +66,59 @@ To use MLlib in Python, you will need
[NumPy](http://www.numpy.org) version 1.4
[^1]: To learn more about the benefits and background of system optimised
natives, you may wish to
watch Sam Halliday's ScalaX talk on [High Performance Linear Algebra
in Scala](http://fommil.github.io/scalax14/#/).
+# Highlights in 2.2
+
+The list below highlights some of the new features and enhancements added
to MLlib in the `2.2`
+release of Spark:
+
+* `ALS` methods for _top-k_ recommendations for all users or items,
matching the functionality
+ in `mllib`
([SPARK-19535](https://issues.apache.org/jira/browse/SPARK-19535)). Performance
+ was also improved for both `ml` and `mllib`
+ ([SPARK-11968](https://issues.apache.org/jira/browse/SPARK-11968) and
+ [SPARK-20587](https://issues.apache.org/jira/browse/SPARK-20587))
+* `Correlation` and `ChiSquareTest` stats functions for `DataFrames`
+ ([SPARK-19635](https://issues.apache.org/jira/browse/SPARK-19635) and
--- End diff --
Ah right thanks for catching that
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