ml-engineer-pro video for your team has been assigned the responsibility of developing a machine learning (ML) solution within Google Cloud to categorize
Your team has been assigned the responsibility of developing a machine learning (ML) solution within Google Cloud to categorize support requests for one of your platforms. After analyzing the requirements, you've chosen to utilize TensorFlow for constructing the classifier, providing you with complete control over the model's code, serving, and deployment. Your intention is to leverage Kubeflow pipelines as the ML platform to expedite the process. In order to save time, you aim to build upon existing resources and utilize managed services, rather than starting from scratch. How should you proceed in building the classifier?