Speaker: Peter Schafhalter

Research Assistant @UC Berkeley RISELab

Peter is a researcher in UC Berkeley's RISELab working in distributed systems and machine learning. He has worked with Ray, RLlib, Tune, and Modin for 1.5 years. He is interested in building high-performance scalable systems that enable AI applications.

Find Peter Schafhalter at

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