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.
SEMICON 2018 Snapshot: Data and the Era of AI
24 Jul 2018
Bill Pierson provides some insights into new developments, initiatives and innovations on display at SEMICON West in San Francisco
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.
Random Forests in kdb+
12 Jul 2018
Using random forest algorithms for machine learning in kdb+ is made easier with embedPy and JupyterQ notebooks. This blog explains how.
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