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Resumen del Editor
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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Lo que los oyentes dicen sobre Machine Learning & Markov Models
Calificaciones medias de los clientesReseñas - Selecciona las pestañas a continuación para cambiar el origen de las reseñas.
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- Thomas
- 12-13-17
quick guide
I quickly looked through some deep learning chapters and enjoyed it, it's not complex and the author did nice job to explain it clearly.
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- Marcelino Cuevas
- 12-11-17
great journey
This book achieved its goal of providing a good top down overview of the algorithms utilized. It's a really good beginning for me to explore random forests methods, examples are simplified but clear enough. I highly recommend for anyone who is just beginning their machine learning journey
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- Sharee
- 12-13-17
thanks
This books...........books that are able to explain the algorithms and other processes without speaking linear algebra.
Great Book! Very practical guide on Machine Learning.
Thanks
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- Catherine
- 12-11-17
very helpful
I find this book helpful and interesting! This book has a great overview including the math involved, which is explained Ina creative but intuitive way.However, I still think this is a great book. The chapter on deep learning (a new chapter) is exceptionally clear and well explained
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- Carol
- 12-11-17
informative
A very informative book. Good advices and tips that work and a great beginners guide for me. I have learned so much from it. I recommend and thank you to the author
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- Connie
- 12-11-17
nice book
Good book on machine learning, you can find a lot of info about different algorithms and other things in this book!
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- Andrea
- 12-11-17
self study
Machine learning has become a pillar of information technology. Here you will find a lot of information that is given for a person to find resources for self study.This book is a good beginner's guide for machine learning. Easy to listen and understand for everybody, contains useful and interesting information.
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- H. Hampton
- 12-11-17
definitely superb
This is such an informative book! It covers most machine learning algorithms divided by genre . From a teaching point of view, the book is quite comprehensive. The book is filled with beautiful graphs and other figures to further help the listener along in their understanding of machine learning. Indeed this book is well presented and I definitely recommend this book!
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- shaliha
- 12-13-17
great overview
Excellent overview. This book is of appropriate depth and breadth and is the first of its kind, i.e., an academic treatment of deep learning. My only complaint is that it doesn't give the reader enough of a chance to solve problems, whether theoretic or hands-on (programming).
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- Jeanne
- 12-11-17
new techniques
Most of the machine learning crash courses are way too long and I couldn't find any free quality material online. This book is not only affordable but it gives off a very simple introduction to machine learning that even people who have no experience with AI can understand. It is surprisingly meaty too talking about data sets and various machine learning techniques in later parts of the book. Even algorithm noobs can use this as a good place to get started.
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