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Vertex AI Pipelines

🔄 Vertex AI MLOps 15m 300 BASE XP

Automating the ML Lifecycle

Training a model in a notebook is easy. Deploying and maintaining it in production requires MLOps. Vertex AI Pipelines allows you to orchestrate ML workflows.

A pipeline might look like this:

  1. Extract data from BigQuery
  2. Preprocess and normalize data
  3. Train a custom model
  4. Evaluate model accuracy against a baseline
  5. If accuracy improves, deploy to a Vertex Endpoint

Pipelines are serverless and defined using the Kubeflow Pipelines (KFP) SDK.

SYNAPSE VERIFICATION
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What is the purpose of Vertex AI Pipelines?
To write SQL queries
To orchestrate and automate the full machine learning lifecycle (MLOps)
To build user interfaces
To serve web traffic