UCL IXN and Vesuvio Labs celebrate third successful year of industrial placement partnership

Alan Abdullah Gulle, Project Manager and Lead Data Scientist @ Vesuvio Labs 2019
Scott Richardson, Head of Advanced Technologies @ Vesuvio Labs 2019
  • Information about consumers’ payment-cycles and history. This helps predict cash flows, produces robust financial forecasts, and defines reliable demographic and segment characteristics.
  • As the volume of data passing through the process increases, business intelligence is refined. More advanced ML techniques are applied producing even more accurate forecasts.
  • Algorithm and feature selection workflow, combined with a hyperparameter tuning pipeline, allow for tailor prediction models to specific time-series probabilities and to foresee specific future events and activities more accurately.
  • The observation and recognition of normal consumer habits helps identify anomalies and changed patterns, perhaps driving greater responsiveness in the business model, or highlighting potentially fraudulent behaviours. As the world moves towards a more digital environment, pattern and exception recognition becomes increasingly valuable to business.
Alan Abdullah Gulle, Project Manager and Lead Data Scientist @ Vesuvio Labs 2019
UCL Main Campus, Kings Cross, London

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VESUVIO LABS

VESUVIO LABS

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