input: Write a function to build and compile a neural network model using TensorFlow and Keras.
  assert build_compile_model((5,)).summary() != None
  assert isinstance(build_compile_model((5,)), tf.keras.Model)
output: def build_compile_model(input_shape):
      import tensorflow as tf
      from tensorflow.keras import layers, models
  
      model = models.Sequential()
      model.add(layers.InputLayer(input_shape=input_shape))
      model.add(layers.Dense(64, activation='relu'))
      model.add(layers.Dense(64, activation='relu'))
      model.add(layers.Dense(1, activation='sigmoid'))
  
      model.compile(optimizer='adam',
                    loss='binary_crossentropy',
                    metrics=['accuracy'])
      return model