What are Bayesian Networks?

Bayesian Networks are graphical models that represent cause-and-effect relationships between variables using probabilities, like a map showing how different factors influence each other. For example, it might show that "rain" increases the probability of "wet grass," which increases the probability of "slippery sidewalks." They're useful for reasoning under uncertainty; you can update your beliefs about one thing (like whether it rained) based on evidence about another (like observing wet grass).