Speaker: Sean Taylor
Sean J. Taylor is a computational social scientist on Facebook's Core Data Science team specializing in field experiments, statistical modeling, and causal inference. His research interests include social influence processes and combining human expertise with machine learning. Sean received his Ph.D. in information systems at NYU’s Stern School of Business and holds a B.S. in economics from The University of Pennsylvania.
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Talk : Forecasting with Prophet
Other talks from track Groking Timeseries & Sequential Data
2019 Tracks
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Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
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Solving Software Engineering Problems with Machine Learning
Interesting machine learning use cases changing how we develop software today, including planned topics touching on infrastructure optimization, developer experience, security, and more.
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Predictive Architectures in the Real World
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.
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Groking Timeseries & Sequential Data
Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.
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Deep Learning in Practice
Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.
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AI Meets the Physical World
Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.