Frequentist vs. Bayesian Statistics with Tensorflow
Probabilistic deep learning
Published in
10 min readJan 5, 2023
Introduction
This article belongs to the series “Probabilistic Deep Learning”. This weekly series covers probabilistic approaches to deep learning. The main goal is to extend deep learning models to quantify uncertainty, i.e. know what they do not know.
The frequentist approach to statistics is based on the idea of repeated sampling and long-run relative frequency. It involves constructing hypotheses about a population and testing them…