docs: def create_classifier(self, metadata, training_data, **kwargs):
          """
          Create classifier.
  
          Sends data to create and train a classifier and returns information about the new
          classifier.
  
          :param file metadata: Metadata in JSON format. The metadata identifies the
          language of the data, and an optional name to identify the classifier. Specify the
          language with the 2-letter primary language code as assigned in ISO standard 639.
          Supported languages are English (`en`), Arabic (`ar`), French (`fr`), German,
          (`de`), Italian (`it`), Japanese (`ja`), Korean (`ko`), Brazilian Portuguese
          (`pt`), and Spanish (`es`).
          :param file training_data: Training data in CSV format. Each text value must have
          at least one class. The data can include up to 3,000 classes and 20,000 records.
          For details, see [Data
          preparation](https://cloud.ibm.com/docs/services/natural-language-classifier/using-your-data.html).
          :param dict headers: A `dict` containing the request headers
          :return: A `DetailedResponse` containing the result, headers and HTTP status code.
          :rtype: DetailedResponse
          """
  
          if metadata is None:
              raise ValueError('metadata must be provided')
          if training_data is None:
              raise ValueError('training_data must be provided')
  
          headers = {}
          if 'headers' in kwargs:
              headers.update(kwargs.get('headers'))
          sdk_headers = get_sdk_headers('natural_language_classifier', 'V1',
                                        'create_classifier')
          headers.update(sdk_headers)
  
          form_data = {}
          form_data['training_metadata'] = (None, metadata, 'application/json')
          form_data['training_data'] = (None, training_data, 'text/csv')
  
          url = '/v1/classifiers'
          response = self.request(
              method='POST',
              url=url,
              headers=headers,
              files=form_data,
              accept_json=True)
          return response