Markov Models: Master the Unsupervised Machine Learning in Python and Data Science with Hidden Markov Models and Real World Applications
暫譯: 馬可夫模型：掌握 Python 中的無監督機器學習與隱馬可夫模型及其在數據科學中的實際應用

Do you want to become a data science Savvy?

If reading about Markov models, stochastic processes, and probabilities leaves you scratching your head, then you have definitely come to the right place.

If you are looking for the most no-nonsense guide that will keep you on the right course during the turbulent ride filled with scientific enigmas, machine learning, and predicting probabilities of hidden, unobservable states, then you have found your perfect companion.

This book will Cover:

• What is Markov models
• How to make predictions with Markov Models
• How to learn without supervision
• How do Markov Models use prediction?
• Hidden Markov Models and how to use them
• The secrets of Markov Chains
• Tips and tricks on how to use Markov Models and machine learning
• Markov Models with Python
• Markov Models Examples and predictions
• How to build and implement HMM algorithms
• How to use Markov Models to master machine learning
• The secrets of Supervised and unsupervised machine learning
• The three components of Hidden Markov Models
• And much, much more!

By the end of this book, I guarantee that you will dive easily into the data science world. Save yourself the hard work and frustration by downloading this book today.

Download your free copy today (Kindle Unlimited only)