Bayesian Neural Networks

Bayesian Neural Networks are a type of machine learning model that understand uncertainty by treating their predictions as probabilities. Unlike traditional neural networks that give a single answer, they estimate a range of possible outcomes, considering the confidence in each. This is achieved by using probabilistic methods to update beliefs based on data, allowing the model to express how certain or uncertain it is about its predictions. This approach improves decision-making in real-world situations where knowing the level of confidence is crucial, making Bayesian Neural Networks valuable in fields like healthcare, finance, and autonomous systems.