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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders.

Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader.

Nov 26, 2018

Today, we’re joined by Stuart Reid, Chief Scientist at NMRQL Research.

NMRQL, based in Stellenbosch, South Africa, is an investment management firm that uses machine learning algorithms to make adaptive, unbiased, scalable, and testable trading decisions for its funds. In our conversation, Stuart and I dig into the way NMRQL uses machine learning and deep learning models to support the firm’s investment decisions. In particular, we focus on techniques for modeling non-stationary time-series, of which financial markets are just one example. We start from first principles and look at stationary vs non-stationary time-series, discuss some of the challenges of building models using financial data, explore issues like model interpretability, and much more. This was a very insightful conversation, which I expect will be very useful not just for those in the fintech space.

Check out the complete show notes for this episode at