Google Professional Machine Learning Engineer Certification Practice Exams
To ace the Google Cloud Machine Learning Certification exam, practice exams are available to help get GCP ML Professional certified.
Scenario 1: Making NLTK Library Available
In a managed Vertex AI Workbench notebook, to try NLTK tokenization, make the library available to the currently running Jupyter kernel by:
- Executing
!pip install nltk --userin a notebook cell
Scenario 2: Running TensorFlow Inference
In a streaming Dataflow pipeline, to run TensorFlow inference while achieving a p95 latency under 150 ms, use:
- Embedding SavedModel in a DoFn
No custom image or batch job is required for these scenarios.
Author's summary: Practice exams help prepare for Google Cloud ML Engineer certification.