[{'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 normalize_greyscale(image_data):\nreturn  (image_data/((0+255)/2)) -1\nmodel = Sequential()\nmodel.add(Lambda(normalize_greyscale ,input_shape=(16,32,1)))\nmodel.add(Conv2D(2, 3, 3, border_mode='valid', input_shape=(16,32,1), activation='relu'))\nmodel.add(MaxPooling2D((4,4),(4,4),'valid'))\nmodel.add(Dropout(0.25))\nmodel.add(Flatten())\nmodel.add(Dense(1))\nfrom keras.utils.visualize_util import plot\nplot(model, to_file='output_for_writeup/model.png')"}, {'role': 'assistant', 'content': "['helper_functions', 'modelling']"}]