neural network in csharp

C# provides the ability to build, train and use neural networks through various libraries such as Accord.NET, TensorFlow.NET, and Keras.NET. Here is an example of how to train and test a neural network using the Accord.NET library.

First, install the Accord.NET package through NuGet:

main.cs
Install-Package Accord
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Then, create a neural network object with the desired number of inputs, hidden layers, and outputs:

main.cs
var network = new ActivationNetwork(new SigmoidFunction(), inputSize, hiddenLayerSize, outputSize);
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Next, create a BackPropagationLearning object for the network:

main.cs
var teacher = new BackPropagationLearning(network);
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Now, you can loop through your training data and adjust the network's weights to minimize the error:

main.cs
double error = double.PositiveInfinity;
while (error > desiredError)
{
    error = teacher.RunEpoch(inputs, outputs); // train
}
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Finally, you can use the trained network to make predictions on new data:

main.cs
double[] prediction = network.Compute(new[] { input1, input2, ..., inputN });
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Of course, the above code is just a simple example. To build more complex neural networks, you may want to use a different library, such as TensorFlow.NET or Keras.NET.