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Overview

Data Labs in Amorphic provides powerful environments for data science and machine learning workflows. It offers flexible options to meet different development needs.

Available Environments​

SageMaker Notebooks​

SageMaker Notebooks provides you with individual Jupyter notebook instances for your data science work. These offer a standalone development environment with built-in support for Python and R kernels. Additionally, they provide integration with AWS Glue for data processing and ability to use custom libraries and dependencies.

SageMaker Studios​

SageMaker Studios provides you with a comprehensive IDE for machine learning development. Studios offer a unified interface for the complete ML workflow and collaborative workspaces for teams. Additionally, they come with advanced integrated tools for ML development, large-scale model training and built-in MLOps capabilities.

Key Features of Data Labs in Amorphic​

  • Flexible Compute: Choose from various instance types and compute configurations to match your workload requirements
  • Native Data Integration: Direct access to datasets, domains and other shared resources in Amorphic
  • Security: VPC isolation and controlled internet/root access for secure development
  • Cost Management: Auto-stop capabilities to optimize resource usage and tag allocation for cost tracking
  • Collaboration: Shared workspaces among other users in Amorphic for collaborative work
  • Quick Create: Set up pre-configured environments with just a few clicks

Getting Started​

Choose Data Lab

Refer to the individual sections for detailed setup and usage instructions.