Advanced Mathematics and Data Analysis With JavaScript

The talk discusses advanced mathematics and data analysis with JavaScript.

JavaScript often performs faster than Python and R, especially for large array sizes, due to its just-in-time compilers optimizing code at runtime.

Standard Lib offers faster loading speeds and more APIs compared to alternatives like Pyodide or WebR, making it a more efficient choice for numerical computing in web browsers.

Yes, Standard Lib plans to apply for Google Summer of Code in 2025.

Standard Lib is a fundamental library for numerical computation on the web, similar to NumPy or SciPy in Python, offering features like fancy indexing and BLAS operations.

WebAssembly can enhance performance, though plain JavaScript sometimes outperforms it for complex functions. WebAssembly is more beneficial for operations like matrix multiplication with large datasets.

Yes, Standard Lib can be integrated with Google Sheets, using familiar syntax and allowing for pseudo-random number generation and other numerical operations directly in spreadsheets.

Interested individuals can contribute to Standard Lib by accessing its GitHub repository, following contributing guidelines, and engaging with the community for support and collaboration.

JavaScript is a good choice due to its ability to perform numeric and scientific computing efficiently in the web browser, with near-native speed thanks to just-in-time compilers.

Gun Joshi is an open source developer and a Google Summer of Code contributor for Standard Lib.