CS 6190 - Probabilistic Modeling

This course focuses on how to use probability theory to model and analyze data. Data in the rel world almost always involves uncertainty. This uncertainty may come from noise in the measurements, missing information, or from the fact that we only have a randomly sampled subset from a larger population. Probabilistic models are an effective approach for understanding such data, by incorporating our assumption and prior knowledge of the world. These ideas are important in many areas of computer science, including machine learning, data mining, natural language processing, computer vision, and image analysis.