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.

Machine learning techniques featured in JupyterQ notebooks

19 Jul 2018 | , , , , , , , ,

Machine learning with kdb+ has been a theme of the Kx blog over the past couple of months because of the release of a series of JupyterQ notebooks on the Kx ML GitHub. As more different kinds of developers work with ML techniques, the uses for kdb+ in ML applications is growing. The release of embedPy, which loads Python into kdb+, so Python variables and objects become q variables and either language can act upon them, has been a catalyst for this trend. With embedPy, Python code and files can be embedded within q code, and Python functions can be called as q functions.

Kx and NASA FDL: Space Weather, GNSS and Exoplanets

10 Jul 2018 | , ,

By Robert Hill Kx is delighted to once more be partnering with the NASA Frontier Development Laboratory (NASA FDL) team on two exciting challenges facing the space sector. This follows from last year’s successful solar activity detection work, which resulted in the ‘FlareNet’ tool (supported by Kx and Lockheed Martin) that demonstrated the potential for