[{'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:import sys\nepochs = 5000\nlearning_rate = 0.001\nhidden_nodes = 100\noutput_nodes = 100\nN_i = train_features.shape[1]\nnetwork = NeuralNetwork(N_i, hidden_nodes, output_nodes, learning_rate)\nlosses = {\'train\':[], \'validation\':[]}\nfor e in range(epochs):\nbatch = np.random.choice(train_features.index, size=128)\nfor record, target in zip(train_features.ix[batch].values,\ntrain_targets.ix[batch][\'cnt\']):\nnetwork.train(record, target)\ntrain_loss = MSE(network.run(train_features), train_targets[\'cnt\'].values)\nval_loss = MSE(network.run(val_features), val_targets[\'cnt\'].values)\nsys.stdout.write("\\rProgress: " + str(100 * e/float(epochs))[:4] \\\n+ "% ... Training loss: " + str(train_loss)[:5] \\\n+ " ... Validation loss: " + str(val_loss)[:5])\nlosses[\'train\'].append(train_loss)\nlosses[\'validation\'].append(val_loss)'}, {'role': 'assistant', 'content': "['helper_functions', 'evaluation', 'modelling']"}]