HMMs for Behavior
Key Takeaways
Théo Michelot discusses applying Hidden Markov Models to complex time-series data from GPS location observations for behavioral analysis in ecology.
Original Description
Théo Michelot has made a career out of tackling tough ecological questions using time-series data. How do scientists turn a series of GPS location observations over time into useful behavioral data? GPS tech has improved to the point that modern data sets are large and complex. In this episode, Théo takes us through his research and the application of Hidden Markov Models to complex time series data. If you have ever wondered what biologists do with data from those GPS collars you have seen on TV, this is the episode for you!
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