Hands-On Markov Models with Python- Implement probabilistic models for learning complex data sequences using Python ecosystem

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September 27, 2018 | ISBN: 978-1788625449 | English | 178 pages | True (PDF, MOBI) + Code | 66 MB
Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn
Key Features

Build a variety of Hidden Markov Models (HMM)
Create and apply models to any sequence of data to analyze, predict, and extract valuable insights
Use natural language processing (NLP) techniques and 2D-HMM model for image segmentation

Book Description

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