Lec 9 Conditional Random Fields 2 3 - Detailed Analysis
Part 1 of Steve Hanov's talk is at www.youtube.com/watch?v=wy_NH1xsB80. In this video he also compares Material based on Jurafsky and Martin (2019): as well as the following excellent resources: ... Shuai Zheng and Sadeep Jayasumana and Bernardino Romera-Paredes and Vibhav Vineet and Zhizhong Su and Dalong Du ... First parts of the talk are: Part 1: Part In this video we actually see how we can perform sequence classification in a linear chain
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![Neural networks [3.1] : Conditional random fields - motivation](https://i.ytimg.com/vi/GF3iSJkgPbA/mqdefault.jpg)
![Neural networks [3.5] : Conditional random fields - computing marginals](https://i.ytimg.com/vi/hjkwp-eDwt8/mqdefault.jpg)

![Neural networks [3.2] : Conditional random fields - linear chain CRF](https://i.ytimg.com/vi/PGBlyKtfB74/mqdefault.jpg)
![Neural networks [4.7] : Training CRFs - general conditional random field](https://i.ytimg.com/vi/QY9k7tJistU/mqdefault.jpg)

![Neural networks [3.6] : Conditional random fields - performing classification](https://i.ytimg.com/vi/pQJvX9U-MyE/mqdefault.jpg)
![Neural networks [3.4] : Conditional random fields - computing the partition function](https://i.ytimg.com/vi/fGdXkVv1qNQ/mqdefault.jpg)