[{'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:def find_weight(data, W,bias, max_iter=15, alpha=0.1):\niter_count = 0\nw_graph = []\nw_bias = []\nerror_sum = 1000\nwhile((error_sum>0.0) & (iter_count<max_iter)):\nerror_sum = 0\nfor data_point in data:\nX = np.array([data_point[0],data_point[1],bias])\nerror = data_point[-1] - predict(X,W)\nW = W + alpha * error * data_point\nbias = bias + error\nw_graph.append(W[:-1])\nw_bias.append(W[:2])\nerror_sum += (error**2)\niter_count+=1\nif(error_sum==0.0):\nprint("CONVERGED AT ",iter_count)\nelse:\nprint("not converged within 15 iterations")\nreturn W,bias,w_graph,w_bias'}, {'role': 'assistant', 'content': 'modelling'}]