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Machine Learning & Markov Models
- Narrated by: Lukas Arnold
- Length: 5 hrs and 17 mins
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Machine Learning & Markov Models
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Summary
Two audiobooks in one. Do not miss out on the bundle book offer! What you'll learn:
Book one: Machine Learning
You will learn the fundamentals of machine learning from algorithms, Python, and supervised and unsupervised learning. Concepts such as decision trees and random forest introduction are explained in detail to assist in grasping the subject matter. You will learn real world applications of machine learning (artificial intelligence) and understand how it will affect humanity in the upcoming years.
The world is constantly changing and evolving. Transportation was revolutionized by cars and planes; however, machine learning will revolutionize the world in which we live from simple day-to-day tasks to even the most complex endeavors.
Book two: Markov Models
In this segment of the bundle, you will learn the mathematics behind Markov model algorithms, artificial intelligence, weather reporting, Bayesian inference, tools, solutions, and much, much more! You will gain insights to the three main problems of Markov models and learn how to overcome them. You will also learn about the real world applications, implications, and theories of Markov models.
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What listeners say about Machine Learning & Markov Models
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Overall5 out of 5 stars
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Performance5 out of 5 stars
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Story5 out of 5 stars
- Lola C Howarth
- 11-12-17
exactly what i wanted
I really love this book very much. This is an excellent guide for the beginners. Highly recommended.
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Overall4 out of 5 stars
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Performance4 out of 5 stars
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Story5 out of 5 stars
- Lemmy
- 11-12-17
mind blowing
The author gives an overview of data science that distinguishes machine learning from data mining, artificial intelligence, etc. I found this useful. He gives specific examples of how machine learning is implemented in marketing and elsewhere. Different types of algorithms, some supported by humans and some not, the machine learning or data mining or other data science
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Overall5 out of 5 stars
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Performance5 out of 5 stars
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Story4 out of 5 stars
- Janet
- 11-12-17
great intro
This is a fantastic Machine Learning book for the absolute beginner. Great introduction to machine learning has been explained and designed for absolute beginners where core algorithms are introduced, clear explanations and functions well explained.
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Overall5 out of 5 stars
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Performance5 out of 5 stars
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Story3 out of 5 stars
- Natasha T Franklin
- 14-12-17
great level
The core ideas and functions well explained. A book to read first and then digging into specialization. Helps to grasp the essentials and to have a base for the next level
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Overall4 out of 5 stars
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Performance5 out of 5 stars
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Story4 out of 5 stars
- aniruth
- 11-12-17
awesome book
An awesome book for individuals who need to pick up information about machine learning. The book manages the diverse fields of machine learning like neural systems and calculations for machine learning. This book is for every one of the fledglings who need to begin finding out about machine gaining sans preparation. The book is likewise useful for the individuals who have no information in machine learning.
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Overall5 out of 5 stars
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Performance5 out of 5 stars
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Story4 out of 5 stars
- Madeleine B Howard
- 11-12-17
great overview
The author gives an overview of data science that distinguishes machine learning from data mining, artificial intelligence, etc. I found this useful. He gives specific examples of how machine learning is implemented in marketing and elsewhere. Different types of algorithms, some supported by humans and some not, the machine learning or data mining or other data science. For anyone who is interested in learning the terminology and scope of approaches that comprise machine learning, this book is current, concise, and informative
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Overall5 out of 5 stars
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Performance4 out of 5 stars
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Story5 out of 5 stars
- Rodney Wagner
- 14-12-17
fabulous
This is explained so as to be helpful as a reference book. Just the other day, I found myself implementing a parallelized feed-forward neural network and quickly picked up the text to see what variations would be helpful. Each topic is generally presented in its basic form with any alternatives and optimizations presented toward the end of the chapter. This meant it was very easy to find what I wanted in seconds.
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Overall5 out of 5 stars
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Performance5 out of 5 stars
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Story4 out of 5 stars
- Katie
- 11-12-17
great book
A great book for people who want to gain knowledge about machine learning. The book deals with the different fields of machine learning like neural networks and algorithms for machine learning. This book is for all the beginners who want to start learning about machine learning from scratch. The book is also very good for those who have no knowledge in machine learning and want to start somewhere.
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Overall4 out of 5 stars
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Performance5 out of 5 stars
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Story4 out of 5 stars
- Bertha
- 11-12-17
great book for beginners
A great book to read to learn machine learning. This is a well explained and concise way to introduce you to random forest algorithm.The author did a great job of clearly and efficiently explaining random forests. Highly recommended especially for the beginners,
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Overall5 out of 5 stars
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Story5 out of 5 stars
- Eula Schultz
- 11-12-17
machine learning
This is an ultimate beginner's guide book.From this book you will learn the introduction to machine learning,an informative write up on artificial intelligence,algorithms in machine learning and much more.I hope this book is able to help you very much.
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