What is probabilistic modeling?

Probabilistic modeling is a framework for capturing uncertainty in data and predictions. It involves creating models that assign probabilities to different outcomes or events, allowing for reasoning and decision-making under uncertainty. Common uses include risk assessment, forecasting, machine learning (e.g., Bayesian networks, Hidden Markov Models), and data analysis where inherent randomness or incomplete information exists. The models often involve estimating probability distributions and using them to make inferences or predictions about unseen data.