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input_dim = X_train.shape[1] input_layer = Input(shape=(input_dim,)) encoded = Dense(32, activation='relu')(input_layer) encoded = Dense(8, activation='relu')(encoded) decoded = Dense(input_dim, activation='linear')(encoded) autoencoder = Model(input_layer, decoded) autoencoder.compile(optimizer='adam', loss='mse') autoencoder.fit(X_train, X_train, epochs=50, batch_size=32)

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