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Pattern Analysis 2018 (QHD 1920)
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Sisällön tarjoaa FAU and Dr. Christian Riess. FAU and Dr. Christian Riess tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
This lecture complements (and builds on top of) the lectures "Introduction to Pattern Recognition" and "Pattern Recognition". In this third edition, we focus on modeling of densities, and how to use these models for analyzing the data. Major topics of this lecture are regression, density estimation, manifold learning, hidden Markov models, conditional random fields, and random forests. The lecture is accompanied by exercises, where theoretical results are practically implemented and applied.
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