Speaker: Amit Nene

Staff Engineer, Tech Lead Manager @Uber

Amit Nene has led engineering teams on the Michelangelo ML Platform and Risk Platform at Uber, driving several projects such as the Palette feature store, feature pipelines and data engineering, and feature transformers. Prior to Uber, he has led several datacenter infrastructure initiatives at companies such as VMware.

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2019 Tracks

  • Predictive Data Pipelines & Architectures

    Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix

  • Sequential Data: Natural Language, Time Series, and Sound

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud