Machine learning: Using embedPy to apply LASSO regression

23 Oct 2018 | , , ,
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By Samantha Gallagher


The use of kdb+ for machine learning in financial technology and other industries is expanding following the release by Kx of the powerful embedPy interface, which allows the kdb+ interpreter to manipulate Python objects, call Python functions, and load Python libraries. Now Python and kdb+ developers can fuse both technologies together, allowing for a seamless application of q’s high-speed analytics and Python’s expansive collection of libraries.

In our latest technical white paper, Kx engineer Samantha Gallagher introduces embedPy, covering both a range of basic tutorials as well as a comprehensive solution to a machine-learning project. EmbedPy is available on GitHub to use with kdb+ V3.5+ and Python 3.5 or higher, for macOS or Linux operating systems and Python 3.6 or higher on the Windows operating system. The installation directory also contains a README.txt about embedPy, and an example directory containing thorough examples.

You can read Samantha’s paper on the Kx Developer’s site, here.


Web Scraping – A Kdb+ Use case

24 Jan 2019 | , , ,

By Abin Saju Web scraping is a method through which human readable content is extracted from a web page using an automated system. The system can be implemented using a bot/web crawler which traverses through domains or through a web browser which mimics human interaction with a page. There are many use cases for the […]

Kx extends relationship with NASA Frontier Development Lab and the SETI Institute

Detection of Exoplanets at NASA FDL with kdb+

13 Dec 2018 | , , , ,

Kx data scientist Espe Aguilera explains a NASA FDL mission to improve the accuracy of finding new exoplanets using machine learning models. The data for the project will come from the Transiting Exoplanet Survey Satellite (TESS), which was launched in April 2018, with the objective of discovering new exoplanets in orbit around the brightest stars in the solar neighborhood.