👉 Notebooks engineering, often associated with platforms like Jupyter Notebook and Google Colab, is a methodology that combines the interactive, web-based nature of notebooks with powerful computational capabilities. These environments allow developers and data scientists to write, execute, and visualize code in a single, integrated interface, making it easier to develop, test, and share complex data science workflows. Notebooks typically support multiple programming languages such as Python, R, and Julia, and they offer features like cell-based execution, where each cell represents a standalone piece of code that can be run independently or in sequence. This approach enhances collaboration, reproducibility, and experimentation by enabling users to document their processes, share results transparently, and easily reproduce analyses. Additionally, notebooks often integrate with cloud storage, version control systems, and machine learning frameworks, providing a comprehensive ecosystem for data science tasks.
