Machine Learning on Terra with Google Cloud [September 15, 2022]

Liz Kiernan
  • Updated

On September 15, 2022, Verily's Dr. Amy Unruh presented a virtual webinar that reviewed different ways you can use Terra for machine learning (ML), with a particular focus on Google Cloud (GC). She used the public Terra workspace for ML on Terra, which you can try yourself. The workspace contains Jupyter Notebooks that use a Keras model to run an image classification task on sample tissue.

Materials

Agenda

In this session, participants learned how to:

  • Run training jobs directly in a workspace notebook
  • Access Vertex AI, BQML (BigQuery ML), and other GC services from a Terra notebook
  • Use Vertex AI for model training and serving (online prediction)
  • Use Vertex AI to do hyperparameter tuning
  • Use the Vertex Experiments API and Managed TensorBoard service to log and monitor your experiments and training progress
  • Build and run ML workflows using Vertex AI Pipelines— using both prebuilt components (task definitions) and your own custom components
  • Train BQML models from BigQuery data and use them for prediction

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