617: Causal Modeling and Sequence Data
Super Data Science: ML & AI Podcast with Jon Krohn
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Exploring Sequence Analytics and Causal Modeling
This chapter delves into the realm of sequence analytics and causal modeling, focusing on the speakers' venture at motif analytics to develop tools for data scientists answering causal questions for customers. They discuss the importance of analyzing sequences of events for rich insights in business applications, bridging the gap between time series data and cross-sectional data. The conversation also touches on the challenges and opportunities presented by rare events and the significance of disaggregated data in uncovering valuable occurrences within an app.
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