JupyterLab vs ML Workspace

JupyterLab is a web-based environment for interactive work with notebooks, code and data. Its workspace brings notebooks, text editors, terminals and custom components together in tabs and splitters. Code consoles act as scratchpads, and kernel-backed documents can run code in files such as Markdown, Python, R and LaTeX. It supports the .ipynb format used by classic Jupyter Notebook, and can view and edit formats including Markdown, images, CSV, JSON, HTML, LaTeX and PDF. Visualization libraries include matplotlib and Plotly; interactive plots or widgets may require additional packages. Extensions can add themes, viewers, editors, output renderers and interface controls, but can execute code in the browser, server and kernel, so only trusted extensions are advised. Real-time collaboration can be enabled with jupyter_collaboration. JavaScript and HTML outputs from notebooks created elsewhere remain hidden until the notebook is trusted. JupyterLab is free, open-source software under a modified BSD license, installed with pip or via a Homebrew command for macOS and Linux. It runs on Linux, macOS, the web and self-hosted systems.

ML Workspace is a self-deployed, web-based development environment for machine learning and data science. It brings browser-accessible Jupyter, JupyterLab, Visual Studio Code, and a Linux desktop GUI together, with libraries such as TensorFlow, PyTorch, Keras, and scikit-learn in its main image. Git-related tools include Ungit, Jupytext, nbdime, and a Jupyter extension for pushing notebooks. TensorBoard supports training monitoring, while Netdata and Glances cover hardware monitoring. The workspace can provide a remote runtime for Jupyter, VS Code, PyCharm, Colab, and Atom Hydrogen, typically through passwordless SSH, and can be accessed through a browser, SSH, or VNC. Image options include minimal, R, Spark, and GPU variants; the GPU flavor requires compatible Nvidia drivers and supports CUDA 11.2. Docker is required, with images deployable on Mac, Linux, and Windows. The project describes token or basic authentication and configurable SSL/HTTPS. It is designed for one user, and at least 2 CPUs and 500 MB of memory are recommended for stable use. The free plan costs nothing.