At some point, we all need to show our work. Most programming work is shared either as raw source code or as a compiled executable. The source code provides complete information, but in a way that’s ...

Overview:  Python and Jupyter offer a simple, powerful setup for beginner-friendly data science learning. Real-world datasets ...

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. Creating, organizing, ...

These days, the industry would have you believe that data and analytics is all being done in the service of AI. And, given that, there's a lot of orientation toward data scientists' seemingly favorite ...

Back in the 1980s, a Stanford University computer scientist and professor named Donald Knuth introduced the concept of “literate programming,” in which a computer program's logic is explained in a ...

Big data refers to datasets that are too large, complex, or fast-changing to be handled by traditional data processing tools. It is characterized by the four V's: Big data analytics plays a crucial ...

Perched atop the Cerro Pachón ridge in the Chilean Andes is a building site that will eventually become the Large Synoptic Survey Telescope (LSST). When it comes online in 2022, the telescope will ...

While you can do some good data analysis with a spreadsheet like Excel, if you want to take your calculations to the next level, you might try Python in a Jupyter notebook instead. Here are some ...

Jupyter Notebook and PyCharm are data science notebook and development tools, respectively. Compare key features to see which tool is best for your business. Choosing the right integrated development ...

Jupyter Notebooks let you combine code, comments, multimedia, and visualizations into an interactive document that can be shared, re-used, and re-worked. Originally developed for data science ...