This repository provides a comprehensive collection of notebooks, code samples, and sample applications designed to demonstrate and facilitate the use of Google Cloud's Vertex AI platform for machine learning and generative AI workflows. It targets ML practitioners and developers looking to leverage Vertex AI's unified platform for building, training, deploying, and managing AI models.

How It Works

The repository is structured into notebooks (further categorized into official and community subdirectories) and community-content. Official notebooks showcase specific Vertex AI services like AutoML, custom model training, Model Garden integrations, Feature Store, and MLOps tools such as Vertex AI Pipelines. The approach emphasizes practical, runnable examples that can be directly executed in cloud environments like Colab, Colab Enterprise, or Vertex AI Workbench, simplifying the learning curve and accelerating adoption.

Quick Start & Requirements

• Install/Run: Notebooks are designed to be run within Google Cloud environments (Colab, Colab Enterprise, Vertex AI Workbench).
• Prerequisites: A Google Cloud project is required. Free trial access is available.
• Resources: Setup involves configuring a Google Cloud project and potentially installing the Vertex AI SDK for Python.
• Links:
  • Vertex AI Jupyter Notebook tutorials: https://cloud.google.com/vertex-ai/docs/notebooks
  • Vertex AI Generative AI GitHub repository: https://github.com/GoogleCloudPlatform/generative-ai
  • Vertex AI documentation: https://cloud.google.com/vertex-ai/docs

Highlighted Details

• Extensive coverage of Vertex AI services, including Model Garden with popular models like Gemini, Gemma, Llama 3, and Claude 3.
• Demonstrations of MLOps capabilities with Vertex AI Pipelines and Google Cloud Pipeline Components.
• Examples for custom model training, deployment, prediction, and Explainable AI.
• Integration with other Google Cloud services like BigQuery and Data Labeling.

Maintenance & Community

This repository is maintained by Google Cloud Platform. Community contributions are welcomed via the Contributing Guide. Feedback and bug reports can be submitted via the Issues page.

Licensing & Compatibility

The repository contains code samples, which are typically provided under permissive licenses allowing for use, modification, and distribution. Specific licensing details for individual code snippets would need to be verified within the respective files or directories. Compatibility for commercial use is generally expected for sample code, but users should verify licensing for production deployments.

Limitations & Caveats

The README explicitly states, "This is not an officially supported Google product. The code in this repository is for demonstrative purposes only." This implies that while the samples are functional, they may not carry the same support guarantees as official Google Cloud products and might be subject to changes or deprecations without formal product lifecycle management.