Speaker: Anil Muppalla

Data Engineer @Spotify

Anil Muppalla is a Data Engineer at Spotify. His current focus building content recommendations on the Home Tab. In the past he has worked on real time data infrastructure for Spotify. He graduated from Georgia Tech with a MS in computer science. His main interest is in solving batch and streaming data problems and data infrastructure in general.

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2019 Tracks

  • 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

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.