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About Hands-On Markov Models with Python
<p><b>Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn</b><p><b>Key Features</b><li>Build a variety of Hidden Markov Models (HMM)<li>Create and apply models to any sequence of data to analyze, predict, and extract valuable insights<li>Use natural language processing (NLP) techniques and 2D-HMM model for image segmentation<p><b>Book Description</b><p>Hidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. The hands-on examples explored in the book help you simplify the process flow in machine learning by using Markov model concepts, thereby making it accessible to everyone.<p>Once you've covered the basic concepts of Markov chains, you'll get insights into Markov processes, models, and types with the help of practical examples. After grasping these...</p></p></p></li></li></li></p></p>
Detailed Information
Author: | Ankur Ankan & Abinash Panda [Ankan, Ankur & Panda, Abinash] |
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Publication Year: | 2018 |
ISBN: | 1788623223 |
Language: | other |
File Size: | 24.3945 |
Format: | |
Price: | FREE |
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