Google Cloud Notebooks are a managed Jupyter Notebook service provided by Google Cloud Platform (GCP). Jupyter Notebooks are popular tools for interactive data analysis, visualization, and machine learning tasks. Google Cloud Notebooks make it easy to create, run, and manage Jupyter notebooks in a cloud-based environment. Here are some key features and information about Google Cloud Notebooks:

1. Managed Environment: Google Cloud Notebooks provide a fully managed Jupyter Notebook environment. You don’t need to worry about setting up infrastructure or managing the underlying servers. Google takes care of the infrastructure for you.

2. Integration with GCP Services: You can easily access and integrate Google Cloud Notebooks with other GCP services like BigQuery, Cloud Storage, and AI Platform. This allows you to work with data stored in GCP and leverage machine learning capabilities.

3. Customizable Environment: You can customize your Jupyter Notebook environment by specifying the machine type, GPU resources, and software packages needed for your data analysis or machine learning tasks.

4. Collaboration: Google Cloud Notebooks support collaboration features, allowing multiple users to work on the same notebook simultaneously. You can also share notebooks with others.

5. Version Control: Google Cloud Notebooks integrate with version control systems like Git, making it easy to track changes and collaborate with a team.

6. Secure and Access-Controlled: Google Cloud Notebooks offer security features such as identity and access management (IAM), ensuring that only authorized users can access your notebooks and data.

7. Data Visualization: You can use popular data visualization libraries like Matplotlib, Seaborn, and Plotly within your Jupyter notebooks to create interactive charts and plots.

8. Scalable: Google Cloud Notebooks can scale to accommodate your compute and memory requirements. You can choose the appropriate machine type to meet your needs.

9. Auto-Saving: Notebooks are automatically saved at regular intervals, reducing the risk of data loss.