Fixes typo in CS example

Adds reference to Wiki for NuGet package

Removes performance setting

Removes unecessary "using"

CNTK.sln

@@ -1579,7 +1579,4 @@ Global
 		{1C6E6C53-1AA7-4B69-913E-B97BB5A872CF} = {3385EBEA-5F97-4B2B-9F30-0E6D7F91B9CA}
 		{CCC07E8E-F33A-4AF7-9F60-93E2AA61C75E} = {3385EBEA-5F97-4B2B-9F30-0E6D7F91B9CA}
 	EndGlobalSection
-	GlobalSection(Performance) = preSolution
-		HasPerformanceSessions = true
-	EndGlobalSection
 EndGlobal

Examples/Evaluation/CSEvalClient/Program.cs

@@ -7,7 +7,6 @@
 
 using System;
 using System.Collections.Generic;
-using System.Diagnostics;
 using System.IO;
 using System.Linq;
 using System.Linq.Expressions;
@@ -22,6 +21,9 @@ namespace Microsoft.MSR.CNTK.Extensibility.Managed.CSEvalClient
     /// This program is a managed client using the CLIWrapper to run the model evaluator in CNTK.
     /// There are four cases shown in this program related to model loading, network creation and evaluation.
     /// 
+    /// To run this program from the CNTK binary drop, you must add the Evaluation NuGet package first.
+    /// Refer to <see cref="https://github.com/Microsoft/CNTK/wiki/Eval-Nuget"/> for information regarding the Evalution NuGet package.
+    /// 
     /// EvaluateModelSingleLayer and EvaluateModelMultipleLayers
     /// --------------------------------------------------------
     /// These two cases require the 01_OneHidden model which is part of the <CNTK>/Examples/Image/MNIST example.
@@ -189,7 +191,7 @@ private static void EvaluateNetworkSingleLayer()
                     model.CreateNetwork(networkDescription, deviceId: -1);
 
                     // Prepare input value in the appropriate structure and size
-                    var inputs = new Dictionary<string, List<float>>() { { "features1", new List<float>() { 1.0f } } };
+                    var inputs = new Dictionary<string, List<float>>() { { "features", new List<float>() { 1.0f } } };
 
                     // We can call the evaluate method and get back the results (single layer output)...
                     var outDims = model.GetNodeDimensions(NodeGroup.Output);