PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #140
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #140: Real Exam Question with Answer & Explanation
Sign in or unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to reveal the answer and full explanation for question #140. The question stem and answer options stay visible for context.
Question
You have been asked to productionize a proof-of-concept ML model built using Keras. The model was trained in a Jupyter notebook on a data scientist's local machine. The notebook contains a cell that performs data validation and a cell that performs model analysis. You need to orchestrate the steps contained in the notebook and automate the execution of these steps for weekly retraining. You expect much more training data in the future. You want your solution to take advantage of managed services while minimizing cost. What should you do?
Options
- AMove the Jupyter notebook to a Notebooks instance on the largest N2 machine type, and
- BWrite the code as a TensorFlow Extended (TFX) pipeline orchestrated with Vertex AI Pipelines.
- CRewrite the steps in the Jupyter notebook as an Apache Spark job, and schedule the execution of
- DExtract the steps contained in the Jupyter notebook as Python scripts, wrap each script in an
Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to see the answer
You've previewed enough free PROFESSIONAL-MACHINE-LEARNING-ENGINEER questions. Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER for full answers, explanations, the timed quiz mode, progress tracking, and the master PDF. Question stem and options stay visible so you can still see what's on the exam.