Probabilistic Models
Probabilistic models are mathematical models that use probability theory to represent uncertainty and make predictions or decisions based on data. In data science and artificial intelligence, probabilistic models are used to model complex systems and make predictions about future events. These models are particularly useful when dealing with incomplete or noisy data, as they can incorporate uncertainty into the analysis. Probabilistic models can be used for a variety of tasks, including classification, regression, clustering, and anomaly detection. They are also used in natural language processing, computer vision, and robotics. Examples of probabilistic models include Bayesian networks, Markov models, and Gaussian processes.
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