Bayesian Networks and Markov Networks: An Intuitive Guide to Structured Uncertainty

# What You Need to Know About Bayesian and Markov Networks Think of these as tools that help AI systems make smarter guesses when they're dealing with incomplete information—like how a doctor might diagnose a disease based on symptoms rather than a complete medical picture. Both approaches map out how different pieces of information connect and influence each other, allowing the system to reason through uncertainty in a structured way. The main difference is simply which direction the connections flow, but both help AI avoid making confident claims when the facts are actually fuzzy or interconnected.