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Today's tutorial is about Conditional Random Fields (CRFs), a more general form of Hidden Markov Models (HMMs). CRFs can be seen as a broadened version of HMMs. When transitioning from a specific model like HMM to a more complex one like CRF, it is essential to question the rationale behind the change and the addition of extra features. This video aims to explore this transition and provide insights into the importance of understanding the underlying concepts in data science.
