BITESIZE | The Why & How of Bayesian Deep Learning, with Vincent Fortuin
Learning Bayesian Statistics
Intro
This chapter delves into the differences between traditional deep learning and Bayesian deep learning, emphasizing the mathematical frameworks and structures of neural networks. It also explores how Bayesian methods involve parameter distributions to measure prediction uncertainty, alongside discussions on model interpretability in statistics.
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