Hands-On Markov Models with Python
This book will help you become familiar with HMMs and different inference algorithms by working on real-world problems. You will start with an introduction to the basic concepts of Markov chains, Markov processes and then delve deeper into understanding hidden Markov models and its types using practical examples.
Offered by
Difficulty Level
Intermediate
Completion Time
5h56m
Language
English
About Book
Who Is This Book For?
Hands-On Markov Models with Python is for you if you are a data analyst, data scientist, or machine learning developer and want to enhance your machine learning knowledge and skills. This book will also help you build your own hidden Markov models by applying them to any sequence of data. Basic knowledge of machine learning and the Python programming language is expected to get the most out of the book
Hands-On Markov Models with Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 5h56m total length
Introduction to Markov Process
Hidden Markov Models
State Inference: Predicting the states
Parameter Inference using Maximum Likelihood
Parameter Inference using Bayesian Approach
Time Series: Predicting Stock Prices
Natural Language Processing: Teaching machines to talk
2D-HMM for Image Processing
Reinforcement Learning: Teaching a robot to cross a maze
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