diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
index d3d082135800e..41e4c41d038af 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
@@ -988,6 +988,7 @@ private[spark] object SerDe extends Serializable {
       val isTransposed = if (m.isTransposed) 1 else 0
       ByteBuffer.wrap(bytes).order(order).asDoubleBuffer().put(m.values)
 
+      out.write(Opcodes.MARK)
       out.write(Opcodes.BININT)
       out.write(PickleUtils.integer_to_bytes(m.numRows))
       out.write(Opcodes.BININT)
@@ -1008,7 +1009,7 @@ private[spark] object SerDe extends Serializable {
       val n = bytes.length / 8
       val values = new Array[Double](n)
       val order = ByteOrder.nativeOrder()
-      val isTransposed = args(3).asInstanceOf[Boolean]
+      val isTransposed = if (args(3).asInstanceOf[Int] == 1) true else false
       ByteBuffer.wrap(bytes).order(order).asDoubleBuffer().get(values)
       new DenseMatrix(args(0).asInstanceOf[Int], args(1).asInstanceOf[Int], values, isTransposed)
     }
diff --git a/python/pyspark/mllib/linalg.py b/python/pyspark/mllib/linalg.py
index a808f1bfc17e9..c3729de752895 100644
--- a/python/pyspark/mllib/linalg.py
+++ b/python/pyspark/mllib/linalg.py
@@ -671,7 +671,8 @@ def __init__(self, numRows, numCols, values, isTransposed=False):
 
     def __reduce__(self):
         return DenseMatrix, (
-            self.numRows, self.numCols, self.values.tostring(), self.isTransposed)
+            self.numRows, self.numCols, self.values.tostring(),
+            int(self.isTransposed))
 
     def toArray(self):
         """
diff --git a/python/pyspark/mllib/tests.py b/python/pyspark/mllib/tests.py
index 1aae57eeb05a5..3671ce8ccc475 100644
--- a/python/pyspark/mllib/tests.py
+++ b/python/pyspark/mllib/tests.py
@@ -85,7 +85,7 @@ def test_serialize(self):
         self._test_serialize(DenseVector(pyarray.array('d', range(10))))
         self._test_serialize(SparseVector(4, {1: 1, 3: 2}))
         self._test_serialize(SparseVector(3, {}))
-        # self._test_serialize(DenseMatrix(2, 3, range(6)))
+        self._test_serialize(DenseMatrix(2, 3, range(6)))
 
     def test_dot(self):
         sv = SparseVector(4, {1: 1, 3: 2})