Pattern Analysis 2016 (HD 1280)

Por: 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.
21 episodios disponibles

Latest episodes of the podcast Pattern Analysis 2016 (HD 1280)

1 - Pattern Analysis 2016 14/04/2016
2 - Pattern Analysis 2016 15/04/2016
3 - Pattern Analysis 2016 21/04/2016
4 - Pattern Analysis 2016 22/04/2016
5 - Pattern Analysis 2016 28/04/2016
6 - Pattern Analysis 2016 29/04/2016
7 - Pattern Analysis 2016 12/05/2016
8 - Pattern Analysis 2016 13/05/2016
9 - Pattern Analysis 2016 02/06/2016
10 - Pattern Analysis 2016 03/06/2016
11 - Pattern Analysis 2016 09/06/2016
12 - Pattern Analysis 2016 10/06/2016
13 - Pattern Analysis 2016 16/06/2016
14 - Pattern Analysis 2016 23/06/2016
15 - Pattern Analysis 2016 24/06/2016
16 - Pattern Analysis 2016 30/06/2016
17 - Pattern Analysis 2016 01/07/2016
18 - Pattern Analysis 2016 07/07/2016
19 - Pattern Analysis 2016 08/07/2016
20 - Pattern Analysis 2016 14/07/2016
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