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An Introduction to Encog Neural Networks for C#

, 26 Jan 2010 CPOL
An introduction to creating neural networks with the Encog Framework for C#.
EncogXORExample
dll
encog-core-cs.dll
log4net.dll
EncogXORExample
bin
Release
encog-core-cs.dll
EncogXORExample.exe
log4net.dll
EncogXORExample.csproj.user
Properties
<?xml version="1.0" encoding="utf-8"?>
<Project ToolsVersion="3.5" DefaultTargets="Build" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
  <PropertyGroup>
    <Configuration Condition=" '$(Configuration)' == '' ">Debug</Configuration>
    <Platform Condition=" '$(Platform)' == '' ">AnyCPU</Platform>
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    <ProjectGuid>{EFD7CB70-08C5-46F1-B28C-5E0855C04FCB}</ProjectGuid>
    <OutputType>Exe</OutputType>
    <AppDesignerFolder>Properties</AppDesignerFolder>
    <RootNamespace>XORExample</RootNamespace>
    <AssemblyName>EncogXORExample</AssemblyName>
    <TargetFrameworkVersion>v3.5</TargetFrameworkVersion>
    <FileAlignment>512</FileAlignment>
  </PropertyGroup>
  <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Debug|AnyCPU' ">
    <DebugSymbols>true</DebugSymbols>
    <DebugType>full</DebugType>
    <Optimize>false</Optimize>
    <OutputPath>bin\Debug\</OutputPath>
    <DefineConstants>DEBUG;TRACE</DefineConstants>
    <ErrorReport>prompt</ErrorReport>
    <WarningLevel>4</WarningLevel>
  </PropertyGroup>
  <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Release|AnyCPU' ">
    <DebugType>pdbonly</DebugType>
    <Optimize>true</Optimize>
    <OutputPath>bin\Release\</OutputPath>
    <DefineConstants>TRACE</DefineConstants>
    <ErrorReport>prompt</ErrorReport>
    <WarningLevel>4</WarningLevel>
  </PropertyGroup>
  <ItemGroup>
    <Reference Include="encog-core-cs, Version=2.3.0.0, Culture=neutral, processorArchitecture=MSIL">
      <SpecificVersion>False</SpecificVersion>
      <HintPath>..\dll\encog-core-cs.dll</HintPath>
    </Reference>
    <Reference Include="log4net, Version=1.2.10.0, Culture=neutral, PublicKeyToken=1b44e1d426115821, processorArchitecture=MSIL">
      <SpecificVersion>False</SpecificVersion>
      <HintPath>..\dll\log4net.dll</HintPath>
    </Reference>
    <Reference Include="System" />
    <Reference Include="System.Core">
      <RequiredTargetFramework>3.5</RequiredTargetFramework>
    </Reference>
    <Reference Include="System.Xml.Linq">
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    </Reference>
    <Reference Include="System.Data.DataSetExtensions">
      <RequiredTargetFramework>3.5</RequiredTargetFramework>
    </Reference>
    <Reference Include="System.Data" />
    <Reference Include="System.Xml" />
  </ItemGroup>
  <ItemGroup>
    <Compile Include="Program.cs" />
    <Compile Include="Properties\AssemblyInfo.cs" />
  </ItemGroup>
  <Import Project="$(MSBuildToolsPath)\Microsoft.CSharp.targets" />
  <!-- To modify your build process, add your task inside one of the targets below and uncomment it. 
       Other similar extension points exist, see Microsoft.Common.targets.
  <Target Name="BeforeBuild">
  </Target>
  <Target Name="AfterBuild">
  </Target>
  -->
</Project>

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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About the Author

JeffHeaton
Architect
United States United States
Jeff Heaton is a data scientist, PhD student and indy publisher. Jeff works primarily in the programming languages Python, R, C#, Java and C/C++. He is an active technology blogger, open source contributor, and author of more than ten books. His areas of expertise include Data Science, Predictive Modeling, Data Mining, Big Data, Business Intelligence and Artificial Intelligence. He is the lead developer for the Encog Machine Learning Framework open source project. Jeff holds a Masters Degree in Information Management from Washington University, is a Senior Member of the IEEE, a Sun Certified Java Programmer and a Fellow of the Life Management Institute.

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