Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK
Mathew Salvaris

Mathew Salvaris
Data Scientist, Microsoft

Mathew Salvaris is a data scientist at Microsoft. Previously, Mathew was a data scientist for a small startup that provided analytics for fund managers; a postdoctoral researcher at UCL’s Institute of Cognitive Neuroscience, where he worked with Patrick Haggard in the area of volition and free will, devising models to decode human decisions in real time from the motor cortex using electroencephalography (EEG); and a postdoc in the University of Essex’s Brain Computer Interface Group, where he worked on BCIs for computer mouse control. Mathew holds a PhD in brain-computer interfaces and an MSc in distributed artificial intelligence.


11:3012:00 Tuesday, 23 May 2017
Level: Intermediate
Mathew Salvaris (Microsoft), Miguel Gonzalez-Fierro (Microsoft)
The speed of a machine-learning algorithm can be crucial in problems that require retraining in real time. Mathew Salvaris and Miguel González-Fierro introduce Microsoft's recently open sourced LightGBM library for decision trees, which outperforms other libraries in both speed and performance, and demo several applications using LightGBM. Read more.