JupyterHub: just released on Marketplace

JupyterHub is a multi-user server for Jupyter notebooks, providing a collaborative environment for data science, machine learning and scientific computing.

A Kubernetes-compatible application available on our Marketplace also includes PyTorch, a popular deep learning framework and CUDA support for GPU acceleration.

JupyterHub allows organizations to serve computational environments to multiple users, making it ideal for teams, academic courses and research labs. PyTorch enables efficient tensor computations and dynamic neural networks, while CUDA support leverages NVIDIA GPUs for accelerated computing.

Use cases

  • Data preprocessing and exploration for machine learning projects
  • Collaborative research in academic and scientific environments
  • Training and fine-tuning deep learning models using PyTorch
  • Accelerated computing tasks using NVIDIA GPUs
  • Interactive coding and visualization for data analysis
  • Educational purposes, such as teaching programming or data science courses
  • Prototyping and experimenting with machine learning algorithms
  • Sharing and reproducing research results in computational sciences
  • Running distributed machine learning workloads across multiple nodes
  • Developing and testing AI applications in a scalable environment

You can deploy JupyterHub with PyTorch and CUDA in your Nebius AI Managed Service for Kubernetes clusters using this Marketplace product — just follow the instructions on the page.

Nebius AI team
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