Pattern Analysis 2016 (Audio) from Dr. Christian Riess

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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Technical details

• RSS: http://feeds.video.uni-erlangen.de/course/itunesu/449/Audio (validate with Livewire, TrueFans, w3.org, podbase, or Cast Feed Validator)
• Apple Podcasts mirror URL: https://pcr.apple.com/id1108031522
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• Most recent enclosure URL: http://itunes.video.uni-erlangen.de/get/file/24202.mp3?src=itunesu

Publishing trends

• Age: 8 years (created 2016-04-26)
• Available episodes: 19
• Stated frequency: series

Episode duration

• Most full episodes are between 82 and 89 minutes

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