Program.cs

using Keras;
using Keras.Layers;
using Keras.Models;
using Numpy;
using System;
using System.IO;

namespace KerasNetXor2
{
    class Program
    {
        static void Main(string[] args)
        {
            //Load train data
            NDarray x = np.array(new float[,] { { 0, 0 }, { 0, 1 }, { 1, 0 }, { 1, 1 } });
            NDarray y = np.array(new float[] { 0, 1, 1, 0 });

            //Build sequential model
            var model = new Sequential();
            model.Add(new Dense(32, activation: "relu", input_shape: new Shape(2)));
            model.Add(new Dense(64, activation: "relu"));
            model.Add(new Dense(1, activation: "sigmoid"));

            //Compile and train
            model.Compile(optimizer: "sgd", loss: "binary_crossentropy", metrics: new string[] { "accuracy" });
            model.Fit(x, y, batch_size: 2, epochs: 1000, verbose: 1);

            //Save model and weights
            string json = model.ToJson();
            File.WriteAllText("model.json", json);
            model.SaveWeight("model.h5");

            //Load model and weight
            var loaded_model = Sequential.ModelFromJson(File.ReadAllText("model.json"));
            loaded_model.LoadWeight("model.h5");

            var result = loaded_model.Predict(x);
            Console.WriteLine("Предсказание для [{0}] = [{1}]", x.ToString(), result.ToString());

        }
    }
}