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
The Exploration of Space Weather at NASA FDL with kdb+
4 Dec 2018
Our society is dependent on GNSS services for navigation in everyday life, so it is critically important to know when signal disruptions might occur. Physical models have struggled to predict astronomic scintillation events. One method for making predictions is to use machine learning (ML) techniques. This article describes how kdb+ and embedPy were used in the ML application.
Machine learning: Using embedPy to apply LASSO regression
23 Oct 2018
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,
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 on the Google Cloud Platform
26 Jun 2018
At Kx25, the international kdb+ user conference held in New York City on May 18th, Kx announced that kdb+ is now available on the Google Cloud Launcher. Antonio Zurlo of Google Cloud Platform (GCP) gave a presentation about Google Cloud and described an example of how to use kdb+ on the GCP.
Classification using K-Nearest Neighbors in kdb+
21 Jun 2018
This blog, in a series about ML and kdb+, gives a demonstration of how to use a JupyterQ notebook to implement K-nearest neighbors in kdb+