Guides to bringing your code from various Machine Learning frameworks to Google Cloud Platform.
The goal is to present recipes and practices that will help you spend less time wrangling with the various interfaces and more time exploring your datasets, building your models, and in general solving the problems you really care about.
- Genomic ancestry inference with deep learning - Ancestry inference on Google Cloud Platform using the 1000 Genomes dataset
- Estimators - A guide to the Estimator interface.
- Model serve - Serve model with Google App Engine and Cloud Endpoints.
- Compute Engine survival training - Introduces a framework for running resilient training jobs on Google Compute Engine.