[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': 'Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:def build_neither_mlp(input_shape, num_output):\n\\tX_input = layers.Input(input_shape)\n\n\\t# First dense layer\n\\tX = layers.Dense(dense_layer_sizes[0], name = \'dense0\')(X_input)\n\\tX = layers.BatchNormalization(name = \'bn0\')(X)\n\\tX = layers.Activation(\'relu\')(X)\n\\tX = layers.Dropout(dropout_rate, seed = 7)(X)\n\n    # Output layer\n\\tX = layers.Dense(num_output, name = \'output\', kernel_regularizer = regularizers.l2(lambd))(X)\n\\tX = layers.Activation(\'sigmoid\')(X)\n\n\\t# Create model\n\\tmodel = models.Model(input = X_input, output = X, name = "neither_model")\n\\treturn model\''}, {'role': 'assistant', 'content': "['modelling']"}]