Machine Learning & Markov Models
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Machine Learning & Markov Models
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Narrated by:
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Lukas Arnold
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By:
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William Sullivan
About this listen
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.
©2017 Healthy Pragmatic Solutions Inc. (P)2017 Healthy Pragmatic Solutions Inc.Listeners also enjoyed...
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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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
- Anonymous User
- 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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Story5 out of 5 stars
- Anonymous User
- 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
- Anonymous User
- 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
- 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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Performance4 out of 5 stars
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Story5 out of 5 stars
- lakshmibai
- 11-12-17
a breeze to follow
Clear and concise introduction to ML. If you don’t have a background in data science, I wouldn’t let this stop you from picking up this book. My own expertise is in mobile web development, which is outside the scope of this book title, but I had no problems going through it.
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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
- Marjorie
- 11-12-17
great follow
This book has helped me progress my baseline understanding of machine learning. The concepts are explained in a smooth fashion way with the right mix of statistical terms. The visual examples and clear instructions made the rest of the book a breeze to follow.
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Overall5 out of 5 stars
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- Anonymous User
- 14-12-17
terrific
For what it is, a brief, nontechnical overview of the field of machine learning, including a discussion of employment opportunities and online courses, this s short audible book is terrific.
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