[{'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:from keras.models import Sequential\nfrom keras.layers import Input, Dropout, Flatten, Convolution2D, MaxPooling2D, Dense, Activation\nfrom keras.callbacks import ModelCheckpoint, Callback, EarlyStopping\nfrom keras.utils import np_utils\nimport numpy as np\nfrom sklearn.cross_validation import train_test_split\nfrom numpy import newaxis\nfrom sklearn.metrics import accuracy_score\ndata = np.load("./data/training_data.npy")\nX = [x[0]/255 for x in data]\ny = [1 if y[1][0] == 1 else 0 for y in data]\nX_cnn = [x[:,:,newaxis] for x in X]\nX_cnn= np.array(X_cnn)\ny = np.array(y)'}, {'role': 'assistant', 'content': "['helper_functions', 'load_data']"}]