What it does

This repository holds sample code and notebooks for Google’s legacy AI Platform Training and Prediction service — the precursor to Vertex AI. You’ll find walkthroughs for training and deploying models with TensorFlow, Keras, scikit-learn, XGBoost, and PyTorch, plus templates for packaging TensorFlow estimators and running jobs on Cloud TPUs.

The interesting bit

The README’s most prominent feature is a giant redirect banner telling you to go elsewhere. Google has effectively turned this into a historical archive — complete with a disclaimer that the content is “not officially maintained.” It’s a rare public admission that a cloud ML service has been fully superseded.

Key highlights

• Covers training, prediction, hyperparameter tuning, and TPU usage across multiple frameworks
• Includes both Jupyter notebook tutorials and bare code guides with README instructions
• Provides trainer package templates for TensorFlow estimators and scikit-learn pipelines
• Contains PyTorch custom container examples for running on AI Platform
• Explicitly unmaintained: Google points all new users to vertex-ai-samples

Caveats

• Content is explicitly not officially maintained by Google
• Many samples target legacy TensorFlow APIs (premade estimators, low-level TF) that have been deprecated in newer TF versions
• The scikit-learn template notes that “examples to be added” — apparently never fulfilled

Verdict

Worth a quick browse if you’re stuck maintaining legacy AI Platform infrastructure or need to migrate old pipelines. Everyone else should follow Google’s own advice and head straight to the Vertex AI samples repo instead.