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ML training and prediction samples for Google Cloud Platform
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This repository offers sample code for Google Cloud AI Platform's Training and Prediction services, demonstrating machine learning workflows across various frameworks like TensorFlow, Keras, scikit-learn, and PyTorch. It targets ML practitioners from novice to advanced levels, providing practical examples for model development on Google Cloud. However, it directs users to the newer vertex-ai-samples
repository for current best practices.
How It Works
The samples are organized by ML tasks (Training, Prediction) and further categorized by popular frameworks. It provides both detailed notebook tutorials for end-to-end walkthroughs and code guides with accompanying READMEs for specific implementations. The approach covers general CPU/GPU usage, specialized hardware like TPUs, and advanced techniques such as hyperparameter tuning and custom container deployment.
Quick Start & Requirements
Installation and setup details are primarily found within individual sample directory READMEs or linked Google Cloud documentation. Specific prerequisites like GPU, TPU, or Python versions vary per sample. Users are strongly encouraged to consult the newer https://github.com/GoogleCloudPlatform/vertex-ai-samples
repository for updated guidance.
Highlighted Details
Maintenance & Community
The repository encourages community contributions via a CONTRIBUTING.md
guide and a Sample Request Page. However, the content is explicitly stated as "not officially maintained by Google."
Licensing & Compatibility
No specific license is mentioned in the provided README content.
Limitations & Caveats
This repository serves as a legacy resource, with Google directing users to the more current https://github.com/GoogleCloudPlatform/vertex-ai-samples
for updated examples and guidance. The content is also noted as not being officially maintained by Google.
3 years ago
Inactive