Preventing Overfishing with Machine Learning and Big Data Analytics (Google Cloud Next '17)

Опубликовано 10 марта 2017, 4:18

Machine learning is becoming a powerful and important aspect of analytics workloads. Amy Unruh and David Kroodsma look at how the Global Fishing Watch project has used Google Cloud Dataflow analytics, Google Cloud Machine Learning, and BigQuery to help monitor and reduce overfishing across the world. In the process, they show you how you can use Dataflow to transform a data stream for distributed training of a deep neural net on the Cloud Machine Learning platform, and use Cloud Machine Learning's support for hyperparameter tuning to optimize performance of the model. You'll also learn how you can access trained models for prediction from Cloud Dataflow pipelines, using Cloud Machine Learning's scalable serving, to augment your pipeline's analytical capabilities.

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