Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

The Jupyter notebook system gives Python users a visual, interactive way to run code, display the results, and share the source with others. But Jupyter notebooks have limited interactivity.

Literate computing has emerged as an important tool for computational studies and open science, with growing folklore of best practices. In this work, we report two case studies—one in computational ...

Computational notebooks have become the tool of choice for many data scientists and practitioners for performing analyses and disseminating results. Despite their increasing popularity, the research ...

Google Colab and Jupyter Notebook are powerful tools for coding and data analysis, each offering unique features and benefits. Compare them to choose the best fit for your needs.

Jupyter Notebooks are a powerful tool for data science, allowing users to write and execute code, visualize data, and document workflows interactively. They are widely used for data exploration, ...

Launching Jupyter Notebook: jupyter notebook Conclusion In this article, we explored the powerful combination of Apache Spark and Jupyter for big data analytics on a Linux platform. By leveraging the ...

In the field of Python-based Data Science projects, the utilization of Jupyter Notebooks is ubiquitous. These interactive and user-friendly environments facilitate seamless integration of code and ...

--- Order: 3 Area: datascience TOCTitle: Data Science Tutorial ContentId: 3c7ae641-e45c-4892-9d8c-7f22bdc549dd PageTitle: Python and Data Science Tutorial in Visual Studio Code DateApproved: 1/9/2023 ...

In notebook environments, users can utilize magic commands like “%%ai” to interact with LLMs. The software supports multiple providers, and users can customize the output format using the “–format” ...

"A set of Jupyter Notebooks on feature selection methods in Python for machine learning. It covers techniques like constant feature removal, correlation analysis, information gain, chi-square testing, ...