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classification ]) # Compiling the model model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']) # Training the model model.fit(X_train, y_train, epochs=20, batch_size=32, validation_data=(X_test, y_test)) You can change hidden layers for further experimentation Moving on