Pre-configured data science notebooks.
Managed JupyterLab with GPU, pre-installed libraries, Git integration, and collaborative editing. From prototype to production.
Pre-configured
Env
Attached
GPU
Real-time
Collab
Integrated
Git
Notebooks, managed.
JupyterLab with GPU and collaboration.
Pre-configured
PyTorch, TensorFlow, scikit-learn, pandas pre-installed.
GPU attached
Attach GPUs to notebooks on demand. T4 to H100.
Collaborative
Real-time collaborative editing like Google Docs.
Git integration
Built-in Git with diff viewer and branch management.
Scheduling
Schedule notebooks to run on cron or trigger.
Custom kernels
R, Julia, Scala, and custom Docker kernels.
Getting started
Launch your first instance in three steps. CLI, console, or API — your choice.
ur ml notebook create ds-env \
--gpu=t4 --libraries=pytorchNotebook patterns.
Data exploration and ML prototyping.
Suggested configuration
Jupyter · GPU · Pre-configured
Estimate your costs
Create detailed configurations to see exactly how much your architecture will cost. Pay for what you use, down to the second.
Configuration 1
Managed Notebooks
Usage
Storage & Artifacts
Cost details
JupyterLab with Git, collaborative editing. Pre-installed libs.
Works seamlessly with
Frequently asked questions
Notebooks, managed.
JupyterLab with GPU, Git, and collaboration.