Fixed build error

Author: Shahab Moradi

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/MulticlassClassification/StochasticDualCoordinateAscent.cs

@@ -16,7 +16,7 @@ public static void Example()
             var examples = DatasetUtils.GenerateRandomMulticlassClassificationExamples(1000);
 
             // Convert native C# class to IDataView, a consumable format for ML.NET functions.
-            var dataView = mlContext.Data.ReadFromEnumerable(examples);
+            var dataView = mlContext.Data.LoadFromEnumerable(examples);
 
             //////////////////// Data Preview ////////////////////
             // Label    Features

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/MulticlassClassification/StochasticDualCoordinateAscentWithOptions.cs

@@ -17,7 +17,7 @@ public static void Example()
             var examples = DatasetUtils.GenerateRandomMulticlassClassificationExamples(1000);
 
             // Convert native C# class to IDataView, a consumable format for ML.NET functions.
-            var dataView = mlContext.Data.ReadFromEnumerable(examples);
+            var dataView = mlContext.Data.LoadFromEnumerable(examples);
 
             //////////////////// Data Preview ////////////////////
             // Label    Features

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/Regression/StochasticDualCoordinateAscent.cs

@@ -15,7 +15,7 @@ public static void Example()
 
             // Create in-memory examples as C# native class and convert to IDataView
             var data = SamplesUtils.DatasetUtils.GenerateFloatLabelFloatFeatureVectorSamples(1000);
-            var dataView = mlContext.Data.ReadFromEnumerable(data);
+            var dataView = mlContext.Data.LoadFromEnumerable(data);
 
             // Split the data into training and test sets. Only training set is used in fitting
             // the created pipeline. Metrics are computed on the test.

docs/samples/Microsoft.ML.Samples/Dynamic/Trainers/Regression/StochasticDualCoordinateAscentWithOptions.cs

@@ -14,7 +14,7 @@ public static void Example()
 
             // Create in-memory examples as C# native class and convert to IDataView
             var data = SamplesUtils.DatasetUtils.GenerateFloatLabelFloatFeatureVectorSamples(1000);
-            var dataView = mlContext.Data.ReadFromEnumerable(data);
+            var dataView = mlContext.Data.LoadFromEnumerable(data);
 
             // Split the data into training and test sets. Only training set is used in fitting
             // the created pipeline. Metrics are computed on the test.