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.
Feature Engineering in kdb+
28 Jun 2018
By Fionnuala Carr As part of Kx25, the international kdb+ user conference held May 18th in New York City, a series of seven JuypterQ notebooks were released and are now available on https://code.kx.com/q/ml/. Each notebook demonstrates how to implement a different machine learning technique in kdb+, primarily using embedPy, to solve all kinds of machine