Automated Machine Learning in kdb+
26 May 2020
This blog gives an overview of the Kx release of an automated machine learning framework (automl) based on the Kx open source machine learning libraries, kdb+ core technology and a number of Python open source libraries accessed via embedPy.
Kx Whitepaper: Option Pricing Methods in kdb+/q
5 Dec 2019
This whitepaper looks at Black-Scholes, Monte Carlo and Quasi-Monte Carlo Methods and the use of Sobol sequences to improve results, in place of more traditional random number generation algorithms.
Kx and DataRobot: Modernizing Financial Markets with AI-Driven Forecasting
19 Nov 2019
Jay’s article outlines how time-aware AI can be used to leverage market data, overcome the cumbersome obstacles of traditional methods and technologies and eliminate the barriers to building and scaling AI-driven investment decision workflows.
Kx Whitepaper: NASA FDL – Disaster Prevention, Progress and Response (Floods)
14 Nov 2019
This whitepaper looks at the problems of predicting the flood susceptibility of an area and predicting the time taken for a river to reach its peak height after a rainfall event. It outlines how Kdb+ can be used to manage and preprocess the associates time-series data
Kx Whitepaper on NLP for Flood Disaster Management at FDL Europe with kdb+
16 Oct 2019
This blog introduces a White Paper and associated notebook explaining the use of Natural Language Processing in a kdb+ architecture to classify tweets relating to flooding events.
Kx Update: Machine Learning Toolkit and JupyterQ Notebooks
20 Sep 2019
The Kx machine learning team has an ongoing project of periodically releasing useful machine learning libraries and notebooks for kdb+. These libraries and notebooks act as a foundation to our users, allowing them to use the ideas presented, and the code provided, to access the exciting world of machine learning with Kx. Check out the latest updates here.