Hidden Markov Model in TensorFlow



**TensorFlow Hands-on Tutorial**


**Outline**

  • Clues in TensorFlow
  • First Model in TensorFlow
  • Convolutional Neural Network (CNN) on Cifar-10
  • Techniques for Deep Learning in TensorFlow
  • Inception V3
  • CNN for Text Classification
  • ** Hidden Markov Model in TensorFlow **
  • Image Captioning in TensorFlow



**Hidden Markov Model in TensorFlow**

The HMM is a sequence model. A sequence model or sequence classifier is a model whose job is to assign a label or class to each unit in a sequence, thus mapping a sequence of observations to a sequence of labels. An HMM is a probabilistic sequence model: given a sequence of units (words, letters, morphemes, sentences, whatever), they compute a probability distribution over possible sequences of labels and choose the best label sequence.

Sequence labeling tasks come up throughout speech and language processing, a fact that isn’t too surprising if we consider that language consists of sequences at many representational levels. [1].

The code can be find at:
https://github.com/MarvinBertin/HiddenMarkovModel_TensorFlow




An example: The MusArt Music-Retrieval System [2]