NuGet info updated

Author: Sergio0694

NeuralNetwork.NET/NeuralNetwork.NET.csproj

@@ -3,7 +3,7 @@
   <PropertyGroup>
     <TargetFramework>netstandard2.0</TargetFramework>
     <RootNamespace>NeuralNetworkNET</RootNamespace>
-    <Version>2.0.0</Version>
+    <Version>2.1.0</Version>
     <Authors>Sergio Pedri</Authors>
     <Company>Sergio Pedri</Company>
     <Description>A TensorFlow-inspired neural network library built from scratch in C# 7.2 for .NET Standard 2.0, with GPU support through cuDNN and native memory management</Description>
@@ -14,9 +14,9 @@
     <PackageTags>cnn, neuralnetwork, deeplearning, ai, cuda, csharp, gpu, net, netstandard</PackageTags>
     <GeneratePackageOnBuild>true</GeneratePackageOnBuild>
     <PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance>
-    <PackageReleaseNotes>• Added computation graph networks (eg. ResNet, Inception)
-• New dataset manipulation APIs
-• Bug fixes and code improvements</PackageReleaseNotes>
+    <PackageReleaseNotes>• Added batch normalization layers
+• APIs refactoring and improvements
+• Bug fixes</PackageReleaseNotes>
   </PropertyGroup>
 
   <PropertyGroup Condition="'$(Configuration)|$(Platform)'=='Release|AnyCPU'">
@@ -35,11 +35,11 @@
     <RestoreProjectStyle>PackageReference</RestoreProjectStyle>
     <AutoGenerateBindingRedirects>true</AutoGenerateBindingRedirects>
     <GenerateBindingRedirectsOutputType>true</GenerateBindingRedirectsOutputType>
-    <AssemblyVersion>2.0.0.0</AssemblyVersion>
+    <AssemblyVersion>2.1.0.0</AssemblyVersion>
     <AssetTargetFallback>
       $(AssetTargetFallback);net45
     </AssetTargetFallback>
-    <FileVersion>2.0.0.0</FileVersion>
+    <FileVersion>2.1.0.0</FileVersion>
   </PropertyGroup>
 
   <ItemGroup>

README.md

@@ -113,7 +113,7 @@ Some complex network structures, like residual networks or inception modules , c
 Computation graph networks are created using the `NetworkManager.NewGraph` API, here's an example:
 
 ```C#
-INeuralNetwork network = NetworkManager.NewGraph(TensorInfo.Image<Alpha8>(28, 28), root =>
+INeuralNetwork network = NetworkManager.NewGraph(TensorInfo.Image<Rgb24>(32,32), root =>
 {
     var conv1 = root.Layer(CuDnnNetworkLayers.Convolutional((5, 5), 20, ActivationType.Identity));
     var pool1 = conv1.Layer(CuDnnNetworkLayers.Pooling(ActivationType.ReLU));