How should you build the classifier?

Your team has been tasked with creating an ML solution in Google Cloud to classify support requests for one of your platforms. You analyzed the requirements and decided to use TensorFlow to build the classifier so that you have full control of the model’s code, serving, and deployment. You will use Kubeflow pipelines for the ML platform. To save time, you want to build on existing resources and use managed services instead of building a completely new model.

How should you build the classifier?
A . Use the Natural Language API to classify support requests
B . Use AutoML Natural Language to build the support requests classifier
C . Use an established text classification model on Al Platform to perform transfer learning
D . Use an established text classification model on Al Platform as-is to classify support requests

Answer: C

Explanation:

the model cannot work as-is as the classes to predict will likely not be the same; we need to use transfer learning to retrain the last layer and adapt it to the classes we need