diff --git a/examples/src/main/python/ml/aft_survival_regression.py b/examples/src/main/python/ml/aft_survival_regression.py
index 9879679829d4d896ffa14aea5c04a6ffdfa7838d..060f0171ffdb5b158c0c4526939ceccf9b63fec7 100644
--- a/examples/src/main/python/ml/aft_survival_regression.py
+++ b/examples/src/main/python/ml/aft_survival_regression.py
@@ -19,7 +19,7 @@ from __future__ import print_function
 
 # $example on$
 from pyspark.ml.regression import AFTSurvivalRegression
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 # $example off$
 from pyspark.sql import SparkSession
 
diff --git a/examples/src/main/python/ml/chisq_selector_example.py b/examples/src/main/python/ml/chisq_selector_example.py
index 8bafb942e0d2736ebaec16b912047c85e5930ada..5e19ef1624c7e8c434835ff4e063280d39036be7 100644
--- a/examples/src/main/python/ml/chisq_selector_example.py
+++ b/examples/src/main/python/ml/chisq_selector_example.py
@@ -20,7 +20,7 @@ from __future__ import print_function
 from pyspark.sql import SparkSession
 # $example on$
 from pyspark.ml.feature import ChiSqSelector
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 # $example off$
 
 if __name__ == "__main__":
diff --git a/examples/src/main/python/ml/dct_example.py b/examples/src/main/python/ml/dct_example.py
index e36fcdeaeed286307044ed8975acfbdda5c87e2f..a4f25df78488608ae70ac46233bb684f2241826c 100644
--- a/examples/src/main/python/ml/dct_example.py
+++ b/examples/src/main/python/ml/dct_example.py
@@ -19,7 +19,7 @@ from __future__ import print_function
 
 # $example on$
 from pyspark.ml.feature import DCT
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 # $example off$
 from pyspark.sql import SparkSession
 
diff --git a/examples/src/main/python/ml/elementwise_product_example.py b/examples/src/main/python/ml/elementwise_product_example.py
index 41727edcdb09e1cf2dc0696fc96c8280e5068c87..598deae886ee138cb3ddac45e79b37e9bf319329 100644
--- a/examples/src/main/python/ml/elementwise_product_example.py
+++ b/examples/src/main/python/ml/elementwise_product_example.py
@@ -19,7 +19,7 @@ from __future__ import print_function
 
 # $example on$
 from pyspark.ml.feature import ElementwiseProduct
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 # $example off$
 from pyspark.sql import SparkSession
 
diff --git a/examples/src/main/python/ml/estimator_transformer_param_example.py b/examples/src/main/python/ml/estimator_transformer_param_example.py
index 0fcae0e3fc225fd2521a086aabc9bddb6c5c998b..3bd3fd30f8e5787f693025e0cc3c58dcf4a52212 100644
--- a/examples/src/main/python/ml/estimator_transformer_param_example.py
+++ b/examples/src/main/python/ml/estimator_transformer_param_example.py
@@ -20,7 +20,7 @@ Estimator Transformer Param Example.
 """
 
 # $example on$
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 from pyspark.ml.classification import LogisticRegression
 # $example off$
 from pyspark.sql import SparkSession
diff --git a/examples/src/main/python/ml/pca_example.py b/examples/src/main/python/ml/pca_example.py
index f1b3cdec7bd7781263c95da49fd8ad5399784614..414629ff88bf9f2e3355894c6f5563b85cf2a323 100644
--- a/examples/src/main/python/ml/pca_example.py
+++ b/examples/src/main/python/ml/pca_example.py
@@ -19,7 +19,7 @@ from __future__ import print_function
 
 # $example on$
 from pyspark.ml.feature import PCA
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 # $example off$
 from pyspark.sql import SparkSession
 
diff --git a/examples/src/main/python/ml/polynomial_expansion_example.py b/examples/src/main/python/ml/polynomial_expansion_example.py
index 08882bcb256f4673ec3d3c520b096ddeddce33cf..9475e33218cfd4e8e1a73791a024c5d44b11a535 100644
--- a/examples/src/main/python/ml/polynomial_expansion_example.py
+++ b/examples/src/main/python/ml/polynomial_expansion_example.py
@@ -19,7 +19,7 @@ from __future__ import print_function
 
 # $example on$
 from pyspark.ml.feature import PolynomialExpansion
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 # $example off$
 from pyspark.sql import SparkSession
 
diff --git a/examples/src/main/python/ml/simple_params_example.py b/examples/src/main/python/ml/simple_params_example.py
index c57e59d01b547f85875e756057d79446499ca2eb..54fbc2c9d05dfdb6883b37a5b024869e5eebd737 100644
--- a/examples/src/main/python/ml/simple_params_example.py
+++ b/examples/src/main/python/ml/simple_params_example.py
@@ -21,9 +21,8 @@ import pprint
 import sys
 
 from pyspark.ml.classification import LogisticRegression
-from pyspark.mllib.linalg import DenseVector
-from pyspark.mllib.regression import LabeledPoint
-from pyspark.sql import SparkSession
+from pyspark.ml.linalg import DenseVector
+from pyspark.sql import Row, SparkSession
 
 """
 A simple example demonstrating ways to specify parameters for Estimators and Transformers.
@@ -42,10 +41,10 @@ if __name__ == "__main__":
     # A LabeledPoint is an Object with two fields named label and features
     # and Spark SQL identifies these fields and creates the schema appropriately.
     training = spark.createDataFrame([
-        LabeledPoint(1.0, DenseVector([0.0, 1.1, 0.1])),
-        LabeledPoint(0.0, DenseVector([2.0, 1.0, -1.0])),
-        LabeledPoint(0.0, DenseVector([2.0, 1.3, 1.0])),
-        LabeledPoint(1.0, DenseVector([0.0, 1.2, -0.5]))])
+        Row(label=1.0, features=DenseVector([0.0, 1.1, 0.1])),
+        Row(label=0.0, features=DenseVector([2.0, 1.0, -1.0])),
+        Row(label=0.0, features=DenseVector([2.0, 1.3, 1.0])),
+        Row(label=1.0, features=DenseVector([0.0, 1.2, -0.5]))])
 
     # Create a LogisticRegression instance with maxIter = 10.
     # This instance is an Estimator.
@@ -77,9 +76,9 @@ if __name__ == "__main__":
 
     # prepare test data.
     test = spark.createDataFrame([
-        LabeledPoint(1.0, DenseVector([-1.0, 1.5, 1.3])),
-        LabeledPoint(0.0, DenseVector([3.0, 2.0, -0.1])),
-        LabeledPoint(0.0, DenseVector([0.0, 2.2, -1.5]))])
+        Row(label=1.0, features=DenseVector([-1.0, 1.5, 1.3])),
+        Row(label=0.0, features=DenseVector([3.0, 2.0, -0.1])),
+        Row(label=0.0, features=DenseVector([0.0, 2.2, -1.5]))])
 
     # Make predictions on test data using the Transformer.transform() method.
     # LogisticRegressionModel.transform will only use the 'features' column.
diff --git a/examples/src/main/python/ml/vector_assembler_example.py b/examples/src/main/python/ml/vector_assembler_example.py
index b955ff00a81951e4e676ef962ff3bf6fec968dce..bbfc316ff2d3334f8f53afab4bd9261d9576d854 100644
--- a/examples/src/main/python/ml/vector_assembler_example.py
+++ b/examples/src/main/python/ml/vector_assembler_example.py
@@ -18,7 +18,7 @@
 from __future__ import print_function
 
 # $example on$
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 from pyspark.ml.feature import VectorAssembler
 # $example off$
 from pyspark.sql import SparkSession
diff --git a/examples/src/main/python/ml/vector_slicer_example.py b/examples/src/main/python/ml/vector_slicer_example.py
index b833a894eb841011356fcaa0f829aeb188340e09..d2f46b190f9a8040737200ff3a83255bbeb3aa1f 100644
--- a/examples/src/main/python/ml/vector_slicer_example.py
+++ b/examples/src/main/python/ml/vector_slicer_example.py
@@ -19,7 +19,7 @@ from __future__ import print_function
 
 # $example on$
 from pyspark.ml.feature import VectorSlicer
-from pyspark.mllib.linalg import Vectors
+from pyspark.ml.linalg import Vectors
 from pyspark.sql.types import Row
 # $example off$
 from pyspark.sql import SparkSession