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Machine Learning in Real-time: Predicting Taxi Fare in NYC

by Big Data LDN

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.

Table of contents

Machine Learning in Real-time: Predicting Taxi Fare in NYC
24mins

About the author

Big Data LDN (London) is a free to attend conference and exhibition, hosting leading data and analytics experts who are ready to equip you with the tools you need to deliver your most effective data-driven strategy. Discuss your business requirements with 130 leading technology vendors and consultants, hear from 150 expert speakers in 9 technical and business-led conference theaters, and network with thousands of fellow data experts.

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