Sean Taylor - Analyzing and Visualizing Event Sequence Data скачать в хорошем качестве

Sean Taylor - Analyzing and Visualizing Event Sequence Data

Analyzing and Visualizing Event Sequence Data by Sean Taylor Visit https://rstats.ai for information on upcoming conferences. Abstract: Many business processes can be represented as event sequence data, especially from product instrumentation in web and mobile applications. However, low-level events are challenging to wrangle, model, and visualize. As a result, analysts typically aggregate data before visualization and estimation, discarding valuable information and introducing bias. In this talk I discuss how to work with event sequences directly, with a focus on exploratory analysis and hypothesis generation, and step through interactive visualizations that support these analysis goals. Bio: Sean J. Taylor is co-founder and chief scientist at Motif Analytics. Previously he was a data scientist and head of Lyft's Rideshare Labs and spent seven years as a research scientist on Facebook's Core Data Science team. Sean's work is at the intersection of experimentation and causal inference, with a focus on applied problems and generating business value using the latest methods. He earned his PhD in Information Systems from NYU’s Stern School of Business as well as a BS in Economics from Wharton. Twitter:   / seanjtaylor   Presented at the 2024 New York R Conference (May 16, 2024) Hosted by Lander Analytics (https://landeranalytics.com)