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Probabilistic Graphical Models 2: Inference (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine [...]
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Introduction to Scientific Machine Learning (edX)

Aug 23rd 2021
Introduction to Scientific Machine Learning (edX)
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Learn the basics of machine learning with hands-on practical examples on engineering applications. This course provides an introduction to data analytics for individuals with no prior knowledge of data science or machine learning. The course starts with an extensive review of probability theory as the language of uncertainty, discusses [...]
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