Markov Models Supervised and Unsupervised Machine Learning: Mastering Data Science & Python - Couverture souple

Sullivan, William

Couverture souple

ISBN 10 : 1976050006 ISBN 13 : 9781976050008

Editeur : CreateSpace Independent Publishing Platform, 2017

Synopsis

Markov Models Supervised and Unsupervised Machine Learning: Mastering Data Science & Python

BONUS Buy a paperback copy of this book NOW and you will get the Kindle version Absolutely FREE via Kindle Matchbook

Do you want to MASTER Data science?

Understand Markov Models and learn the real world application to accurately predict future events

Extend your knowledge of machine learning, python programming & algorithms

What you'll Learn

Mathematics Behind Markov Algorithms

3 Main Problems Of Markov Models And How To Overcome Them

Uses And Applications For Machine Learning

Python Programming

Speech Recognition

Weather Reporting

The Markov Rule And Markov’s Model

Fundamental Axioms Of Statistics And Probability

Solutions

Theories

Artificial Intelligence

Bayesian Inference

Important Tools Used With HMM

And Much, Much, More!

The objective of this book is to teach you the essentials at the most fundamental level

You will learn the ins and outs of machine learning, and its real world applications

Also, specifically you will discover practical implementations of Markov Models in python programming

This book offers high value and is the greatest investment in your knowledge base you can make that will benefit you in the long run

Why not take this opportunity to take advantage now and get ahead of everyone else?

Other books can easily retail for $100s- $1000s of dollars!

Get equipped with the knowledge you need to advance yourself today at an affordable price

What are you waiting for?

Don't miss out on this opportunity!

Grab Your Copy Now!

First time audible listeners get a 30 day free-trial and 2 free audible books when signing up for the first time.

Audible Link: https://www.audible.com/t2/title?asin=B0767LQ99X

A propos du livre

Présentation de l'éditeur

Markov Models Supervised and Unsupervised Machine Learning: Mastering Data Science & Python

BONUS Buy a paperback copy of this book NOW and you will get the Kindle version Absolutely FREE via Kindle Matchbook

Do you want to MASTER Data science?

Understand Markov Models and learn the real world application to accurately predict future events

Extend your knowledge of machine learning, python programming & algorithms

What you'll Learn

Mathematics Behind Markov Algorithms

3 Main Problems Of Markov Models And How To Overcome Them

Uses And Applications For Machine Learning

Python Programming

Speech Recognition

Weather Reporting

The Markov Rule And Markov’s Model

Fundamental Axioms Of Statistics And Probability

Solutions

Theories

Artificial Intelligence

Bayesian Inference

Important Tools Used With HMM

And Much, Much, More!

The objective of this book is to teach you the essentials at the most fundamental level

You will learn the ins and outs of machine learning, and its real world applications

Also, specifically you will discover practical implementations of Markov Models in python programming

This book offers high value and is the greatest investment in your knowledge base you can make that will benefit you in the long run

Why not take this opportunity to take advantage now and get ahead of everyone else?

Other books can easily retail for $100s- $1000s of dollars!

Get equipped with the knowledge you need to advance yourself today at an affordable price

What are you waiting for?

Don't miss out on this opportunity!

Grab Your Copy Now!

First time audible listeners get a 30 day free-trial and 2 free audible books when signing up for the first time.

Audible Link: https://www.audible.com/t2/title?asin=B0767LQ99X

Détails de l'édition

• Éditeur: CreateSpace Independent Publishing Platform
• Date d'édition: 2017
• Langue: anglais
• ISBN 10: 1976050006
• ISBN 13: 9781976050008
• Reliure: Broché
• Nombre de pages: 124
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible