Disaster prediction research at NASA FDL with kdb+/q, ML and AI
27 Aug 2019
Kx collaborate with the U.S. Geological Survey (USGS) in a project to to determine where machine learning could assist in the area of flood prediction to improve their ability to best prepare and respond when a natural disaster occurs.
Machine Learning Toolkit Update: Cross-Validation and ML Workflow in kdb+
23 Jul 2019
The Kx machine learning team has an ongoing project of periodically releasing useful machine learning libraries and notebooks for kdb+. This release relates to the areas of cross-validation and standardized code distribution procedures for incorporating both Python and q distribution. Such procedures are used in feature creation through the FRESH algorithm and cross-validation within kdb+/q.
White Paper on 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.
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.