Jupyter Notebooks (.ipynb files) are an open-source, web-based application for interactive data science and computing. Their core strength is combining live code, equations, visualisations, and narrative text into a single, shareable document, making them fundamental for data science, machine learning, and research. I have selected the JavaScript version of the IPYNB.
Core Capabilities:
Interactive Code supports step-by-step execution and refinement.
Benefits of Jupyter Notebooks: Rich Output includes comprehensive outputs, tables, charts, and visualisations. Combined Content offers a unified environment for integrating code, formatted text (Markdown), and dynamic visuals.
Primary Uses
Knowledge Sharing & Education: Excellent for creating interactive learning materials and tutorials because of features like Markdown, runnable code, and instant feedback. Notebooks are also modular and easily reusable.
Professional Communication & Presentation: Tools can turn notebooks into dynamic slideshows that combine code, results, and narrative. They are also powerful, interactive sales tools through the embedding of live visualisations
Collaboration & Reproducibility: Notebooks help teams work together and ensure research is reproducible by capturing the whole workflow, including data handling, analysis, and conclusions.
Notebooks are great for quick tests and explaining things, especially when creation is helped by an AI like Claude
Use the .ipynb file for troubleshooting, lessons, or sales demos.
