diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py
index 3d8883b486e4c..a770bad32ecd2 100755
--- a/python/pyspark/ml/tests.py
+++ b/python/pyspark/ml/tests.py
@@ -950,6 +950,13 @@ def test_fit_maximize_metric(self):
                          "Best model should have zero induced error")
         self.assertEqual(1.0, bestModelMetric, "Best model has R-squared of 1")
 
+    def test_param_grid_type_coercion(self):
+        lr = LogisticRegression(maxIter=10)
+        paramGrid = ParamGridBuilder().addGrid(lr.regParam, [0.5, 1]).build()
+        for param in paramGrid:
+            for v in param.values():
+                assert(type(v) == float)
+
     def test_save_load_trained_model(self):
         # This tests saving and loading the trained model only.
         # Save/load for CrossValidator will be added later: SPARK-13786
diff --git a/python/pyspark/ml/tuning.py b/python/pyspark/ml/tuning.py
index 0c8029f293cfe..1f4abf5157335 100644
--- a/python/pyspark/ml/tuning.py
+++ b/python/pyspark/ml/tuning.py
@@ -115,7 +115,11 @@ def build(self):
         """
         keys = self._param_grid.keys()
         grid_values = self._param_grid.values()
-        return [dict(zip(keys, prod)) for prod in itertools.product(*grid_values)]
+
+        def to_key_value_pairs(keys, values):
+            return [(key, key.typeConverter(value)) for key, value in zip(keys, values)]
+
+        return [dict(to_key_value_pairs(keys, prod)) for prod in itertools.product(*grid_values)]
 
 
 class ValidatorParams(HasSeed):