This is the Windows app named Jupyter Docker Stacks whose latest release can be downloaded as docker-stackssourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS:
Jupyter Docker Stacks
DESCRIPTION:
Jupyter Docker Stacks provides a curated set of ready-to-run Docker container images that bundle Jupyter applications with popular data science and computing tools, enabling users to quickly start working in a reproducible environment. These stacks support a range of use cases, from lightweight base notebook images to full featured environments that include scientific computing libraries, machine learning tools, and IDE-like notebook interfaces, all within Docker containers that run consistently across machines. Users can pull a particular stack image and launch a Jupyter server without worrying about installing Python, R, or complex dependencies themselves — everything needed is baked into the container. This makes the stacks especially useful for education, demos, collaborative coding, and CI/CD workflows where consistent environments are crucial, and it integrates smoothly with cloud platforms, JupyterHub deployments, and Binder for interactive sharing.
Features
- Docker images preloaded with Jupyter tools and extensions
- Support for JupyterLab, Notebook, and other frontends
- Multiple images tailored for data science, ML, and research
- Variants with CPU and GPU (CUDA) support
- Consistent, reproducible environments across systems
- Documentation and examples for customizing stacks
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/jupyter-docker-stacks.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.