[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:car_ind = np.random.randint(0, len(cars))\nnotcar_ind = np.random.randint(0, len(notcars))\ncar_image = mpimg.imread(cars[car_ind])\nnotcar_image = mpimg.imread(notcars[notcar_ind])\ncar_features, car_hog_image = single_img_features(car_image, color_space=color_space, spatial_size=spatial_size,\nhist_bins=hist_bins, orient=orient,\npix_per_cell=pix_per_cell, cell_per_block=cell_per_block,hog_channel=hog_channel,\nspatial_feat=spatial_feat, hist_feat=hist_feat, hog_feat=hog_feat,\nvis=True)\nnotcar_features, notcar_hog_image = single_img_features(notcar_image, color_space=color_space, spatial_size=spatial_size,\nhist_bins=hist_bins, orient=orient,\npix_per_cell=pix_per_cell, cell_per_block=cell_per_block,hog_channel=hog_channel,\nspatial_feat=spatial_feat, hist_feat=hist_feat, hog_feat=hog_feat,\nvis=True)\nimages=[car_image, car_hog_image, notcar_image, notcar_hog_image]\ntitles=['car image', 'car HOG image', 'notcar image', 'notcar HOG image']\nfig = plt.figure(figsize=(12,3))\nvisualise(1, 4, images, titles)"}, {'role': 'assistant', 'content': 'load_data'}]