Nick Radcliffe

Nick is a practising data scientist with over 30 years experience, from neural networks and genetic algorithms on parallel systems in the late 1980s, through parallel machine learning and 3D visualisation software as a founder of Quadstone, from 1995, to novel modelling methods (e.g. uplift modelling) in the early 2000s. Since 2007 , he has run Edinburgh data science specialists Stochastic Solutions.

Nick enjoys using his deep knowledge of underlying algorithms to fashion tailored solutions to practical business problems for clients including Barclays, Sainsburys, T-Mobile and Skyscanner, and has a particular interest in testing and correctness in data science.


Twitter handle

@njr0

Twitter handle

@njr0

Homepage

stochasticsolutions.com

Homepage

stochasticsolutions.com

Git*hub|lab

https://github.com/tdda

Git*hub|lab

https://github.com/tdda

Institute / Company

Stochastic Solutions Limited & Department of Mathematics, University of Edinburgh

Institute / Company

Stochastic Solutions Limited and Department of Mathematics, University of Edinburgh


Session

09-04
14:45
30min
Constrained Data Synthesis
Nick Radcliffe

We introduce a method for creating synthetic data "to order" based on learned (or provided) constraints and data classifications. This includes "good" and "bad" data.

Track 2 (Baroja)