Overview

  • Jupyter notebook-based development environment
  • Single development environment—explore, train, deploy ML models via code
  • Unified platform
  • Seamless, scalable, sustainable, speedy—models have 80% fewer lines of code than competitors

Notebooks

  • Google or user managed options
  • User managed:
    • Deep Learning VM Images
    • Customizable environment
  • Packaged with JupyterLab
  • Pre-installed suite of packages e.g. TensorFlow, PyTorch
  • GPU support
  • Sync with GitHub
  • Can run notebooks on Dataproc

Graph View