Speaker: Adam Jelley, Dataiku
Synopsis: 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:
- Understand the problem before building models
- Do not add features for the sake of features
- Try as many algorithms as possible
- Simplify your pipeline before deployment

Filmed at Big Data LDN 2019

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