Bayesian Inference: The Best 5 Models and 10 Best Practices for Machine Learning

Author(s): Anil Tilbe

Originally published on Towards AI.

The advantages, top 5 models, and top 10 best practices for applying Bayesian inference to machine learning problems

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Bayesian inference is a popular machine learning technique that allows for an algorithm to make predictions based on prior beliefs [1]. In Bayesian inference, the posterior distribution of predictors (derived from observed data) is updated based on new evidence. I will explore the various benefits of Bayesian inference and provide an overview of how it can be used in machine learning. Additionally, I will go over some common applications of Bayesian inference and discuss some of the challenges that have been faced when using this technique.

Bayesian inference is a probabilistic approach to machine learning that provides estimates of the… Read the full blog for free on Medium.

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Published via Towards AI