What is Data Science Virtual Machine?
Azure Data Science Virtual Machines (DSVM) are preconfigured VM images with all essential tools for data science and machine learning. Data scientists can start immediately without spending hours on installation.
Core Features
- Preinstalled ML frameworks: TensorFlow, PyTorch, Scikit-learn
- Development environments: Jupyter, VS Code, RStudio
- GPU support with CUDA and cuDNN
- Azure ML SDK and CLI preinstalled
- Automatic tool updates
Typical Use Cases
- Quick start for ML projects
- Training deep learning models
- Exploration and prototyping
Benefits
- No installation time: immediately productive
- Consistent environment for teams
- Flexible scaling as needed
- Cost-effective: pay only when using
Integration with innFactory
As a Microsoft Solutions Partner, innFactory supports you with Data Science VMs: team setup, integration with Azure ML, GPU optimization, and cost management.
Frequently Asked Questions
What tools are preinstalled?
Python, R, Julia, TensorFlow, PyTorch, Scikit-learn, Jupyter, VS Code, Azure ML SDK, Power BI Desktop, and many more. Over 50 tools ready to use immediately.
Are GPU variants available?
Yes, DSVM is available on NC-series (NVIDIA Tesla) and NDv2 (NVIDIA A100) VMs. CUDA and cuDNN are preinstalled.
Windows or Linux?
Both available. Ubuntu-based DSVMs are optimized for deep learning, Windows DSVMs for Power BI and SQL Server integration.
How does DSVM differ from Azure ML Compute?
DSVM for interactive development and exploration. Azure ML Compute for scalable training jobs and production pipelines.
