Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Hands-On Markov Models with Python

You're reading from Hands-On Markov Models with Python Implement probabilistic models for learning complex data sequences using the Python ecosystem

Product type Paperback

Published in Sep 2018

Publisher Packt

ISBN-13 9781788625449

Length 178 pages

Edition 1st Edition

Languages

Python

Concepts

Statistics

Authors (2):

Ankur Ankan

Abinash Panda

View More author details

Table of Contents (11) Chapters

Preface

1. Introduction to the Markov Process FREE CHAPTER

2. Hidden Markov Models

3. State Inference - Predicting the States

4. Parameter Learning Using Maximum Likelihood

5. Parameter Inference Using the Bayesian Approach

6. Time Series Predicting

7. Natural Language Processing

8. 2D HMM for Image Processing

9. Markov Decision Process

10. Other Books You May Enjoy

Leave a review - let other readers know what you think

Code

Currently, there are no packages in Python that support learning using Bayesian learning and it would be really difficult to write the complete code to fit in this book. And even though there are a lot of advantages to using Bayesian learning, it is usually computationally infeasible in a lot of cases. For these reasons, we are skipping the code for Bayesian learning in HMMs.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

Ankan

Ankan

Ankur Ankan is a BTech graduate from IIT (BHU), Varanasi. He is currently working in the field of data science. He is an open source enthusiast and his major work includes starting pgmpy with four other members. In his free time, he likes to participate in Kaggle competitions.

See other products by Ankan

Panda

Panda

Abinash Panda has been a data scientist for more than 4 years. He has worked at multiple early-stage start-ups and helped them build their data analytics pipelines. He loves to munge, plot, and analyze data. He has been a speaker at Python conferences. These days, he is busy co-founding a start-up. He has contributed to books on probabilistic graphical models by Packt Publishing.

See other products by Panda

Other recommended products

Related to this chapter

Statistics Crash Course for Beginners

Statistics Crash Course for Beginners

Through both theoretical and practical study with Python, this course will get you up to speed with all you need to know about statistics in programming—a core study of machine learning.

Mar 2021 10h 58m

Hands-On Reinforcement Learning with R

Hands-On Reinforcement Learning with R

Reinforcement Learning is an exciting part of machine learning. It has uses in technology from autonomous cars to game playing, and creates algorithms that can adapt to environmental changes. This book helps to understand how to implement RL with R, and explores interesting practical examples, such as using tabular Q-learning to control robots.

Dec 2019 12h 4m

Mastering Machine Learning Algorithms

Mastering Machine Learning Algorithms

This book is your guide to quickly get to grips with the most widely used machine learning algorithms. As a data science professional, this book will help you design and train better machine learning models to solve a variety of complex problems, and make the machine learn your requirements.

May 2018 19h 12m

Bayesian Analysis with Python

Bayesian Analysis with Python

Bayesian inference uses probability distributions and Bayes' theorem to build flexible models. The book uses PyMC3 to abstract all the mathematical and computational details from this process allowing readers to solve a wide range of problems in data science.

Dec 2018 11h 52m

Scala for Machine Learning

Scala for Machine Learning

Scala is becoming the language of choice for software engineers and data scientists who analyze large data sets. This trend has been reinforced by the wide acceptance of Scala based frameworks such as Apache Spark and Kafka. As a functional language, Scala is particularly suited for extracting knowledge through supervised, unsupervised or reinforcement learning techniques. Being object-oriented, Scala ensured the construction of robust and maintainable software solutions. This book introduces the most common used machine learning models as implemented in Scala

Sep 2017 24h 40m

Mastering Java Machine Learning

Mastering Java Machine Learning

Master key Java machine learning libraries and their applications with the help of real-world case studies. Explore advanced machine learning techniques such as anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning.

Jul 2017 18h 32m

Mastering Machine Learning Algorithms

Mastering Machine Learning Algorithms

A new second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problems, updated to include Python 3.8 and TensorFlow 2.x as well as the latest in new algorithms and techniques.

Jan 2020 26h 36m

Mastering Reinforcement Learning with Python

Mastering Reinforcement Learning with Python

This book focuses on expert-level explanations and implementations of scalable reinforcement learning algorithms and approaches. Starting with the fundamentals, the book covers state-of-the-art methods from bandit problems to meta-reinforcement learning. You’ll also explore practical examples inspired by real-life problems from the industry.

Dec 2020 18h 8m

Mastering Predictive Analytics with R

Mastering Predictive Analytics with R

R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems. Updated with revamped examples and to the latest version of R, this book is designed to be both a guide and a reference for moving beyond the basics of predictive modeling.

Aug 2017 14h 56m

Python Deep Learning

Python Deep Learning

The book will help you learn deep neural networks and their applications in computer vision, generative models, and natural language processing. It will also introduce you to the area of reinforcement learning, where you'll learn the state-of-the-art algorithms to teach the machines how to play games like Go and Atari.

Jan 2019 12h 52m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.