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Which Vertex AI capability should an ML Engineer use to run a CUSTOM training job using their own PyTorch / TensorFlow / scikit-learn code, packaged as a container — with GCP managing the compute lifecycle?
ACloud Memorystore
BVertex AI custom training (with prebuilt or custom container images)
CCloud DNS
DManually SSHing into a VM and running `python train.py`
Answer & Solution
Correct answer: B. Vertex AI custom training (with prebuilt or custom container images)
Vertex AI custom training is the managed custom-code runtime (per PMLE §3.2). Manual SSH doesn't scale; the others aren't training.
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