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