vertex-ai-samples and applied-ai-engineering-samples
These are ecosystem siblings—both official Google Cloud repositories providing complementary sample collections for the same Vertex AI platform, with the former offering broader ML/AI workflows and the latter focusing specifically on generative AI implementations.
About vertex-ai-samples
GoogleCloudPlatform/vertex-ai-samples
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
Includes reusable AI agent "Skills" for common tasks like model deployment, fine-tuning (Gemini and open models), and inference with GenAI SDKs across Python, JavaScript, Go, Java, and C#. Organized into official service-specific notebooks, community contributions, and hands-on examples covering AutoML, custom training, Feature Store, Explainable AI, and ML Metadata—runnable directly in Colab, Colab Enterprise, or Vertex AI Workbench.
About applied-ai-engineering-samples
GoogleCloudPlatform/applied-ai-engineering-samples
This repository compiles code samples and notebooks demonstrating how to use Generative AI on Google Cloud Vertex AI.
Covers foundation models, evaluation frameworks, RAG/grounding techniques, and agentic AI patterns across Vertex AI, with specialized content for Gemini prompting, GenAI evaluation services, and Vertex AI Search integration. The repository also includes AI/ML infrastructure blueprints for large-scale workloads and operationalization guides for research models from Google DeepMind. Supporting tools like RAG Playground enable hands-on experimentation with retrieval methods and LLMs using LangChain integration.
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