[{'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 baseline_model():\nmodel = Sequential()\nmodel.add(Convolution2D(24, 3, 3, border_mode='valid', input_shape=(66, 100, 3), activation='relu'))\nmodel.add(Convolution2D(36, 5, 5, activation='relu', border_mode='same', W_constraint=maxnorm(3)))\nmodel.add(Convolution2D(48, 5, 5, activation='relu', border_mode='same'))\nmodel.add(Convolution2D(64, 5, 5, activation='relu', border_mode='same'))\nmodel.add(Convolution2D(64, 3, 3, activation='relu', border_mode='same'))\nmodel.add(Flatten())\nmodel.add(Dense(400, activation='relu'))\nmodel.add(Dense(100, activation='relu'))\nmodel.add(Dense(50, activation='relu'))\nmodel.add(Dense(10, activation='relu'))\nmodel.add(Dense(output_dim=1,activation='relu'))\nmodel.compile(loss='mean_squared_error', optimizer='adam')\nprint(model.summary())\nreturn model"}, {'role': 'assistant', 'content': "['modelling']"}]