Google Professional Machine Learning Engineer
Get started today
Ultimate access to all questions.
Ultimate access to all questions.
You are part of a team that develops advanced deep learning models using the TensorFlow framework, and you conduct multiple machine learning experiments every week. This frequent experimentation makes it challenging to keep track of all the experiment runs. You need a straightforward solution to efficiently track, visualize, and debug these ML experiment runs on Google Cloud, with minimal additional code or infrastructure overhead. Considering your needs, what would be the most effective approach?
Explanation:
The correct answer is A. Setting up Vertex AI Experiments to track metrics and parameters and configuring Vertex AI TensorBoard for visualization is the most effective approach. Vertex AI Experiments is specifically designed for tracking ML experiments on Google Cloud, simplifying the logging of metrics and parameters without needing custom code. Additionally, Vertex AI seamlessly integrates with TensorBoard, allowing you to visualize training logs and metrics directly within the Experiments interface. This centralized solution minimizes the need for additional code or infrastructure setup compared to other options that involve Cloud Functions, VMs, and manual setup.