Welcome to the AI Platform sample code repository. This repository contains samples for how to use AI Platform products.
The repository is organized by products:
- AI Platform (Unified)
- AI Platform Training
- AI Platform Prediction
- scikit-learn
- TensorFlow
- XGBoost
- Tools AI Platform Prediction tools
- AI Platform Optimizer
- AI Platform Pipelines
- AI Platform Notebooks
- AI Hub
We highly recommend that you start with our Quick Start Sample.
This repository is organized based on the available products on AI Platform, and the typical Machine Learning problems that developers are trying to solve. For instance, if you are trying to train a model with scikit-learn, you will find the sample under training/sklearn/structured/base directory. AI Platform also supports xgboost, TensorFlow, and PyTorch.
Please refer to the README.md file in each sample directory for more specific instructions.
If you’re looking for our guides on how to do Machine Learning on Google Cloud Platform (GCP) using other services, please checkout our other repositories:
- ML on GCP, which has guides on how to bring your code from various ML frameworks to Google Cloud Platform using things like Google Compute Engine or Kubernetes.
- Keras Idiomatic Programmer This repository contains content produced by Google Cloud AI Developer Relations for machine learning and artificial intelligence. The content covers a wide spectrum from educational, training, and research, covering from novices, junior/intermediate to advanced.
- Professional Services, common solutions and tools developed by Google Cloud's Professional Services team.
Only Googlers may contribute to this repo. If you are a Googler, please see go/cloudai-notebook-workflow for instructions.
For common issues and solutions, please check our troubleshooting page.
Please use the issues page to provide feedback or submit a bug report.
This is not an officially supported Google product. The code in this repository is for demonstrative purposes only.