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Machine Learning in Real-time: Predicting Taxi Fare in NYC
Big Data LDN 2019 | Machine Learning in Real-time: Predicting Taxi Fare in NYC | Adam Jelley
What you'll learn
Today, the benefit of Machine Learning is conditioned to its deployment in real-time. In this talk, Adam Jelley, Data Scientist, will explain how to deploy a real-time taxi fare prediction engine to power an Uber-like application. Along the cycle of developing such a project, he will highlight key lessons learned, like understand the problem before building models, do not add features for the sake of features, try as many algorithms as possible, and simplify your pipeline before deployment.