Big Data LDN 2019: Machine Learning in real time: predicting taxi fare in NYC

Speaker: Adam Jelley, Dataiku Synopsis: Today, the benefit of Machine Learning is conditioned to its deployment in realtime. In this talk, Adam Jelley, Data Scientist, will explain how to deploy a realtime taxi fare prediction engine to power an Uberlike application. Along the cycle of developing such a project, he will highlight key lessons learned: Understand the problem before building models Do not add features for the sake of features Try as many algorithms as possible Simplify your pi