Fire engine staff optimisation at the London Fire Brigade

Machine Learning / supervised learning / gradient boosted trees / optimisation

By André Richter, ASI Fellow, May 2017 The emergency responses of the London Fire Brigade (LFB) are complex operations involving a variety of specialised skills. Not all skills are shared by all firefighters, so unanticipated disruptions to the team composition (for instance due to sickness) frequently render teams unable to…

Detecting Anomalies in the Real World - at Strata + Hadoop London!

Strata + Hadoop Conference / Machine Learning / anomaly detection / balanced forests / random forest / Data Science / supervised learning / unsupervised learning / fraud detection / foreground detection / Data Engineering / Events / ASI / Alessandra Stagliano

A couple of weeks ago, I was lucky enough to give a talk at the Hardcore Data Science track at Strata London, “the Lollapalooza of big data conferences”. The quality of other speakers were intimidatingly good (key people from the Scikit-learn and Google Deepmind, are just two examples) and the…