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Today's tutorial will focus on Conditional Random Fields (CRFs), which can be seen as a more general form of Hidden Markov Models (HMMs). The video discusses how transitioning from a specific HMM to a more complex CRF in data science involves considering the reasons for making the model more intricate and adding extra features. The tutorial also introduces the concept of using CRFs to improve model performance and storytelling in machine learning.