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.
Machine Learning Toolkit Update: Multi-parameter FRESH and updated utilities
25 Apr 2019
This latest toolkit release, is the first in a series of planned releases in 2019 that will add updates to the functionality of the FRESH (Feature Extraction based on Scalable Hypothesis tests) algorithm and the addition of a number of accuracy metrics, preprocessing functions and utilities. In conjunction with code changes, modifications to the namespace structure of the toolkit have been made to streamline the code and improve user experience.
2018 most read blogs: Python, Machine Learning, Cloud and kdb+ Performance
19 Dec 2018
In 2018 the most-read blogs on kx.com were about kdb+ and Python, machine learning, cloud and kdb+ performance benchmarks. The expansion of the use of kdb+ and Kx technologies in new industries like space research, transportation tech and precision manufacturing was also chronicled in 2018 blogs.
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.
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,