diff --git a/docs/en/ml/limitations.asciidoc b/docs/en/ml/limitations.asciidoc
index 5a36652cb90..3e245cb602f 100644
--- a/docs/en/ml/limitations.asciidoc
+++ b/docs/en/ml/limitations.asciidoc
@@ -84,7 +84,7 @@ Missing fields might be expected due to the structure of the data and therefore
 do not generate poor results.
 
 For more information about `missing_field_count`,
-see {ref}/ml-datacounts.html[Data Counts Objects].
+see {ref}/ml-jobstats.html#ml-datacounts[Data Counts Objects].
 
 
 [float]
@@ -118,7 +118,7 @@ are not certain that you need this option or if you experience performance
 issues, edit your job configuration to disable this option.
 
 For more information, see
-{ref}/ml-apimodelplotconfig.html[Model Plot Config].
+{ref}/ml-job-resource.html#ml-apimodelplotconfig[Model Plot Config].
 
 Likewise, when you create a single or multi-metric job in {kib}, in some cases
 it uses aggregations on the data that it retrieves from {es}. One of the
diff --git a/docs/en/ml/overview.asciidoc b/docs/en/ml/overview.asciidoc
index 625c65e58bf..6382050ea29 100644
--- a/docs/en/ml/overview.asciidoc
+++ b/docs/en/ml/overview.asciidoc
@@ -10,7 +10,7 @@ concepts from the outset will tremendously help ease the learning process.
 
 Machine learning jobs contain the configuration information and metadata
 necessary to perform an analytics task. For a list of the properties associated
-with a job, see {ref}ml-job-resource.html[Job Resources].
+with a job, see {ref}/ml-job-resource.html[Job Resources].
 
 [float]
 [[ml-dfeeds]]