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Notebook Environments

Notebook environments are interactive computing platforms that combine code execution, rich text, visualizations, and multimedia in a single document. They enable iterative development, data exploration, and collaborative sharing by allowing users to write and run code in discrete cells, with immediate output displayed inline. Popular examples include Jupyter Notebook, Google Colab, and R Markdown, widely used in data science, machine learning, education, and research.

Also known as: Jupyter Notebook, Interactive Notebooks, Computational Notebooks, Notebooks, IPython Notebook
🧊Why learn Notebook Environments?

Developers should learn notebook environments for rapid prototyping, data analysis, and reproducible research, as they facilitate exploratory coding and visualization without switching between tools. They are essential in data science workflows for tasks like model training, statistical analysis, and creating interactive reports, and are valuable in educational settings for teaching programming concepts with live examples.

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