BITESIZE | Hacking Bayesian Models for Better Performance, with Luke Bornn
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BITESIZE | Hacking Bayesian Models for Better Performance, with Luke Bornn
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About this listen
Today’s clip is from episode 131 of the podcast, with Luke Bornn.
Luke and Alex discuss the application of generative models in sports analytics. They emphasize the importance of Bayesian modeling to account for uncertainty and contextual variations in player data.
The discussion also covers the challenges of balancing model complexity with computational efficiency, the innovative ways to hack Bayesian models for improved performance, and the significance of understanding model fitting and discretization in statistical modeling.
Get the full discussion here.
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Transcript
This is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.