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Unsupervised Machine Learning Hidden Markov Models in Python

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Unsupervised Machine Learning Hidden Markov Models in Python

Unsupervised Machine Learning Hidden Markov Models in Python, HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.

Created by Lazy Programmer Inc.

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What you'll learn
  • Understand and enumerate the various applications of Markov Models and Hidden Markov Models
  • Understand how Markov Models work
  • Write a Markov Model in code
  • Apply Markov Models to any sequence of data
  • Understand the mathematics behind Markov chains
  • Apply Markov models to language
  • Apply Markov models to website analytics
  • Understand how Google's PageRank works
  • Understand Hidden Markov Models
  • Write a Hidden Markov Model in Code
  • Write a Hidden Markov Model using Theano
  • Understand how gradient descent, which is normally used in deep learning, can be used for HMMs

Requirements
  • Familiarity with probability and statistics
  • Understand Gaussian mixture models
  • Be comfortable with Python and Numpy
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