About this document
Hidden Markov Models in NLP by Jmpol John is a document available to read on EtoBox.
1) The document discusses Hidden Markov Models (HMM), which are used to model observable sequences that are produced by an underlying hidden Markov process. 2) An example of a coin tossing HMM is provided, where the hidden states are which coin is being tossed (fair or biased), and the observations are heads or tails. 3) The key problems in HMMs are calculating the probability of an observation sequence given the model, and calculating the probability of a hidden state sequence given the model. Exact com
- Author
- Jmpol John
- Language
- EN