diff --git a/src/Microsoft.ML/Models/BinaryClassificationEvaluator.cs b/src/Microsoft.ML/Models/BinaryClassificationEvaluator.cs
index c08f516909..e0a4eae826 100644
--- a/src/Microsoft.ML/Models/BinaryClassificationEvaluator.cs
+++ b/src/Microsoft.ML/Models/BinaryClassificationEvaluator.cs
@@ -18,7 +18,7 @@ public sealed partial class BinaryClassificationEvaluator
         /// The trained PredictionModel to be evaluated.
         /// </param>
         /// <param name="testData">
-        /// The test data that will be predicted and used to evaulate the model.
+        /// The test data that will be predicted and used to evaluate the model.
         /// </param>
         /// <returns>
         /// A BinaryClassificationMetrics instance that describes how well the model performed against the test data.
diff --git a/src/Microsoft.ML/Models/ClassificationEvaluator.cs b/src/Microsoft.ML/Models/ClassificationEvaluator.cs
index ddf3958b99..c8bec8642f 100644
--- a/src/Microsoft.ML/Models/ClassificationEvaluator.cs
+++ b/src/Microsoft.ML/Models/ClassificationEvaluator.cs
@@ -18,7 +18,7 @@ public sealed partial class ClassificationEvaluator
         /// The trained multi-class classification PredictionModel to be evaluated.
         /// </param>
         /// <param name="testData">
-        /// The test data that will be predicted and used to evaulate the model.
+        /// The test data that will be predicted and used to evaluate the model.
         /// </param>
         /// <returns>
         /// A ClassificationMetrics instance that describes how well the model performed against the test data.
diff --git a/src/Microsoft.ML/Models/RegressionEvaluator.cs b/src/Microsoft.ML/Models/RegressionEvaluator.cs
index 66e784da9b..8c2daa53f0 100644
--- a/src/Microsoft.ML/Models/RegressionEvaluator.cs
+++ b/src/Microsoft.ML/Models/RegressionEvaluator.cs
@@ -18,7 +18,7 @@ public sealed partial class RegressionEvaluator
         /// The trained PredictionModel to be evaluated.
         /// </param>
         /// <param name="testData">
-        /// The test data that will be predicted and used to evaulate the model.
+        /// The test data that will be predicted and used to evaluate the model.
         /// </param>
         /// <returns>
         /// A RegressionMetrics instance that describes how well the model performed against the test data.
diff --git a/src/Microsoft.ML/Runtime/EntryPoints/CodeGen/TransformGenerators.cs b/src/Microsoft.ML/Runtime/EntryPoints/CodeGen/TransformGenerators.cs
index c946f1360f..30146264c6 100644
--- a/src/Microsoft.ML/Runtime/EntryPoints/CodeGen/TransformGenerators.cs
+++ b/src/Microsoft.ML/Runtime/EntryPoints/CodeGen/TransformGenerators.cs
@@ -200,7 +200,7 @@ protected override void GenerateContent(IndentingTextWriter writer, string prefi
         {
             writer.WriteLine("[Module(");
             _compName = prefix + component.LoadNames[0];
-            var name = Name ?? PrettyPrintDiaplayName(component.LoadNames[0]);
+            var name = Name ?? PrettyPrintDisplayName(component.LoadNames[0]);
             using (writer.Nest())
             {
                 writer.WriteLine("Name = \"{0}\",", name);
@@ -460,7 +460,7 @@ protected override void GenerateParameter(IndentingTextWriter w, string type, st
         private void GenerateParameterAttribute(IndentingTextWriter w, string displayName, object defaultValue, string description,
             string parent = null, string parentType = null, string parentValue = null)
         {
-            w.WriteLine("[Help(Display = @\"{0}\", ToolTip = \"{1}\")]", PrettyPrintDiaplayName(displayName), description);
+            w.WriteLine("[Help(Display = @\"{0}\", ToolTip = \"{1}\")]", PrettyPrintDisplayName(displayName), description);
             if (parent != null)
                 w.WriteLine("[Relevancy(Key = \"{0}\", Values = new object[] {{ {1}.{2} }})]", parent, parentType, parentValue);
             if (defaultValue != null)
@@ -468,7 +468,7 @@ private void GenerateParameterAttribute(IndentingTextWriter w, string displayNam
             w.WriteLine("[ModuleParameter]");
         }
 
-        private string PrettyPrintDiaplayName(string displayName)
+        private string PrettyPrintDisplayName(string displayName)
         {
             var sb = new StringBuilder();
             bool first = true;
diff --git a/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationBinaryMacro.cs b/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationBinaryMacro.cs
index 4ad7621844..302a71245c 100644
--- a/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationBinaryMacro.cs
+++ b/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationBinaryMacro.cs
@@ -37,7 +37,7 @@ public sealed class SubGraphOutput
 
         public sealed class Arguments
         {
-            // This is the data used in the cross validataion. It will be split into k folds
+            // This is the data used in the cross validation. It will be split into k folds
             // and a model will be trained and evaluated for each fold.
             [TlcModule.OptionalInput]
             [Argument(ArgumentType.Required, HelpText = "The data set", SortOrder = 1)]
diff --git a/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationMacro.cs b/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationMacro.cs
index 686fb787a9..1cb950f939 100644
--- a/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationMacro.cs
+++ b/src/Microsoft.ML/Runtime/EntryPoints/CrossValidationMacro.cs
@@ -35,7 +35,7 @@ public sealed class SubGraphOutput
 
         public sealed class Arguments
         {
-            // This is the data used in the cross validataion. It will be split into k folds
+            // This is the data used in the cross validation. It will be split into k folds
             // and a model will be trained and evaluated for each fold.
             [TlcModule.OptionalInput]
             [Argument(ArgumentType.Required, HelpText = "The data set", SortOrder = 1)]