[{'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:#dependencies\nimport pandas as pd\nimport keras\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\nfrom matplotlib import style\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import MinMaxScaler\nfrom sklearn import preprocessing, svm  \nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation, Flatten\nfrom keras.layers import Embedding\nimport math\nfrom keras import metrics\nimport seaborn as sns\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.metrics import confusion_matrix\nfrom keras.models import Sequential\nfrom keras.layers import Dense, LSTM \nimport matplotlib.pyplot as plt\nplt.style.use('fivethirtyeight')\nimport datetime as dt\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.tree import DecisionTreeRegressor\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.metrics import confusion_matrix\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.linear_model import LogisticRegression, LinearRegression\nfrom sklearn.model_selection import TimeSeriesSplit\nfrom sklearn.svm import SVR\nfrom xgboost import XGBRegressor"}, {'role': 'assistant', 'content': 'helper_functions'}]