Google Professional Machine Learning Engineer
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As an ML researcher evaluating multiple deep learning model architectures and hyperparameter configurations, you need to implement a robust solution to track each model iteration, visualize key metrics, gain insights into model internals, and optimize training performance.
To ensure your solution has the most efficient and powerful approach for comparing models and the strongest visualization capabilities, how should you build this solution?
A
Use Vertex AI TensorBoard for in-depth visualization and analysis, and use BigQuery for experiment tracking and analysis.
B
Use Vertex AI TensorBoard for visualizing training progress and model behavior, and use Vertex AI Feature Store to stove and manage experiment data for analysis and reproducibility.
C
Use Vertex AI Experiments for tracking iterations and comparison, and use Vertex AI TensorBoard for visualization and analysis of the training metrics and model architecture.
D
Use Vertex AI Experiments for tracking iterations and comparison, and use BigQuery and Looker Studio for visualization and analysis of the training metrics and model architecture.