Enhancing Your kdb+/q Toolkit: Real World Examples of Adverbs

12 Apr 2017 | , , , ,

Nuša Žnuderl's latest blog post uses five real-world examples to demonstrate how kdb+/q coders can improve their results by using adverbs and not using looping constructs. Long-term the benefit is vastly improved performance from doing things in the “q way.” In her blog Nuša writes: "Similar to the English language, adverbs in q augment operations to allow an application on lists. They make code shorter, clearer and almost always more efficient than the alternative loopy modus operandi – all of which are qualities that differentiate code written by proficient q users from the rest."

Using q in Machine Learning with Neural Network and Clustering Examples

4 Apr 2017 | , , , , ,

Tokyo-based kdb+ programmer, and algorithmic quantitative analyst, Mark Lefevre recently gave a couple of talks about using high-performance machine learning with kdb+ at the Kx Community Tokyo Meetup. His talk “Using Q to Read Japanese” focused on utilizing neural networks and how supervised learning can be used in q to teach a machine to recognize Japanese characters from handwritten images. His second talk, “Kx for Wine Tasting” focused on utilizing the k-means clustering algorithm and unsupervised learning in q to teach a machine to appreciate wine!

On Implementing an XML Standard In Kx

6 Mar 2017 | , , ,

London-based kdb+ developer Eoghan Page recently developed a solution to generate FpML (Financial products Markup Language) for some interest rate derivatives, specifically interest rate swaps, tenor basis swaps and forward rate agreements. In his informative blog post with coding examples, Eoghan describes how he originally had done a similar task in Python, which became an "unmaintainable giant," so he decided to start from scratch and use kdb+. After you read the article, check out his code on GitHub.

Distributed Computing in kdb+

21 Dec 2016 | , , ,

Kx financial engineer, Connor Gervin, gave a talk at a Kx Community NYC Meetup in 2015 that is worth revisiting. Connor described kdb+’s built-in multithreading and multiprocessing capabilities, which are an essential part of every serious kdb+ programmer's’ toolkit. With these features, programmers can make the best use of multicore hardware when solving increasingly complex problems over ever-expanding datasets.