Choose from Colab Enterprise or Vertex AI Workbench. Access every capability in Vertex AI Platform to work across the entire data science workflow—from data exploration to prototype to production.
Natively analyze your data with a reduction in context switching between services
Data to training at scale. Build and train models 5x faster, compared to traditional notebooks
Scale up model development with simple connectivity to Vertex AI services
Simplified access to data and in-notebook access to machine learning with BigQuery, Dataproc, Spark, and Vertex AI integration.
Take advantage of the power of infinite compute with Vertex AI Training for experimentation and prototyping, to go from data to training at scale.
Using Colab Enterprise or Vertex AI Workbench you can implement your training and deployment workflows on Vertex AI from one place.
Colab Enterprise combines the notebook developed by Google Research and used by over 7 million data scientists with Google Cloud enterprise level security and compliance. Get started quickly with a zero-config, serverless, and collaborative environment.
AI-powered code assistance features like code completion and code generation make it easier to build AI/ML models in Python, reducing the need to write repetitive code, so you can focus on your data and models.
Vertex AI Workbench provides a JupyterLab experience and advanced customization capabilities.
Vertex AI notebooks provide fully managed, scalable, enterprise-ready compute infrastructure with security controls and user management capabilities.
Explore data and train ML models with easy connections to Google Cloud's big data solutions.
Develop and deploy AI solutions on Vertex AI with minimal transition.
|Simplified data access|
Extensions will seamlessly connect to the entire data estate including BigQuery, Data Lake, Dataproc, and Spark. Seamlessly scale up or scale out depending on your analytic and AI needs.
|Explore data sources using a catalog|
Write SQL, Spark queries from a syntax-aware, auto-complete enabled notebook cell.
Integrated, intelligent visualization tools will provide easy insights into data.
|Hands-off, cost-effective infrastructure|
All aspects of the compute are managed. Idle timeout and auto shutdown will optimize total cost of ownership.
|Enterprise security, simplified|
Out-of-the-box Google Cloud security controls. Single sign-on and simple authentication to other Google Cloud services.
|Data Lake and Spark in one place|
Whether you use TensorFlow, PyTorch, or Spark, you can run any engine from Vertex AI Workbench.
|Deep Git, training, and MLOps integration|
With few clicks, plug notebooks into established Ops workflows. Use notebooks for distributed training, hyper-parameter optimization, or scheduled or triggered continuous training. Deep integration with Vertex AI services brings MLOps into the notebook without the need to rewrite code or new workflows.
Kubeflow Pipelines integration to use Notebooks as an ideal, tested, and verified deployment target.
Share output of periodically updated notebook cells for reporting and bookkeeping purposes.