Name: 스토리텔 언리미티드
Brand: Storytel
SKU: 7777
Price: 13800 KRW
Availability: InStock

Ankur Ankan

Abinash Panda

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.

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 fundamentals, you’ll move on to learning about the different algorithms used in inferences and applying them in state and parameter inference. In addition to this, you’ll explore the Bayesian approach of inference and learn how to apply it in HMMs.

In further chapters, you’ll discover how to use HMMs in time series analysis and natural language processing (NLP) using Python. You’ll also learn to apply HMM to image processing using 2D-HMM to segment images. Finally, you’ll understand how to apply HMM for reinforcement learning (RL) with the help of Q-Learning, and use this technique for single-stock and multi-stock algorithmic trading.

By the end of this book, you will have grasped how to build your own Markov and hidden Markov models on complex datasets in order to apply them to projects.

Packt Publishing

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

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Storytel

스토리텔 스토리텔 언리미티드로 매월 무제한 청취와 독서가 가능하며, 방대한 오디오북과 이북 카탈로그에 접근할 수 있습니다.