[{'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 training_step(i, update_test_data):\nbatch = range(i*batchsize,(i*batchsize)+batchsize)\nbatch_X = trainData[oneHotFeatureCols+readFeatureCols].iloc[batch]\nbatch_Y = trainData[oneHotLabelCols].iloc[batch]\nmax_learning_rate = 0.05\nmin_learning_rate = 0.001\ndecay_speed = 100.0\nlearning_rate = min_learning_rate + (max_learning_rate - min_learning_rate) * math.exp(-i/decay_speed)\nif update_test_data:\na, c = sess.run([accuracy, cross_entropy], {X: testData[oneHotFeatureCols+readFeatureCols], Y_: testData[oneHotLabelCols], pkeep: 1.0})\nprint(str(i) + " : test accuracy:" + str(a) + " test loss: " + str(c))\nsess.run(train_step, {X: batch_X, Y_: batch_Y, pkeep: 0.75, lr: learning_rate})'}, {'role': 'assistant', 'content': "['modelling']"}]