AI Platform Notebooks is a managed service that offers an integrated JupyterLab environment in which machine learning developers and data scientists can create instances running JupyterLab that come pre-installed with the latest data science and machine learning frameworks in a single click. Notebooks is integrated with BigQuery, Cloud Dataproc, and Cloud Dataflow, making it easy to go from data ingestion to preprocessing and exploration, and eventually model training and deployment.
This directory contains multiple Notebooks showing Machine Learning examples:
- Notebooks auto-shutdown: This script will continuously monitor the CPU load and will shut down the instance if the load is less than a particular threshold (for a specified amount of time). It also can check Docker CPU utilization and shut down the host VM as described above.
- Notebook executor: This repository contains the logic that can be used to schedule Jupyter notebooks from anywhere (local, GCE, GCP Notebooks) to the Google Cloud Deep Learning VM. You can read more about the usage of this tool here.
- Notebook CI showcase: A fully functional continuous integration and continuous deployment system for Jupyter Notebooks.
- Nova Agent: Allows you to execute notebooks directly from your Jupyter UI. Nova and its corresponding compute workload runs on a separate Compute Engine instance using Nteract papermill.
- Nova Jupyterlab extensions: Nova Plugin.
- Notebook Deployment Manager: Automating AI Platform Notebook Instance Creation With GCP Deployment Manager.
- Terraform: Deploy a Notebook instance using Terraform.
If you have further questions, or encounter issues using AI Platform Notebooks, open an issue or reach out at our team's forum: https://groups.google.com/forum/#!forum/google-dl-platform