Machine Learning & Markov Models Audiobook by William Sullivan
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Title: Machine Learning & Markov Models Author: William Sullivan Narrator: Lukas Arnold Format: Unabridged Length: 5 hrs and 17 mins Language: English Release date: 12-02-17 Publisher: Healthy Pragmatic Solutions Inc Ratings: 4.5 of 5 out of 29 votes Genres: Science & Technology, Technology

Publisher's 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.

Members Reviews: empty learning it contribute to me no real data. in 2min search on Google I would get more.

Not meant to be an audio book What disappointed you about Machine Learning & Markov Models? I stopped after the beginning of chapter 3 once I read a review from another person who returned this book, after they reached chapter 5, for the same reason. This book contains a list of terms, definitions, and algorithms and explains them in a very dry way. I was hoping for an explanation of what machine learning is and maybe even how it is used. This book provided a brief overview of that, but then went into harsh detail about the types of algorithms associated with machine learning. My initial thought before purchasing this book was - if this book were to dive into detail, which it did, it would probably do so in a way where the information could be learned audibly, which it didn't. This is probably a great book to read, but I wouldn't recommend it for listening. Would you ever listen to anything by William Sullivan again? Probably not. It seems his books are more meant to be read. You didnt love this book... but did it have any redeeming qualities? It was incredibly informative. It's just simply that the knowledge contained isn't easily absorbed in an audible fashion.

that was great Good for understanding machine learning mathematics. It has succinct explanations for equations so most of time you do not need to worry about understanding math

feel better Despite its title, this book provides a superb introduction to much of machine learning. Similarly, its treatment of Deep Learning is easily one of the best. The care with which the authors wrote is obvious, starting with systematically defining terms, a mark of true scholarship in my opinion. I can't over-recommend this book. And of course, the authors are all deeply involved (no pun intended) in developing Deep Learning in the first place. It doesn't get any better.

superb introducttion This book is a model of technical explanation -- clear, precise, well-organized, and relentlessly helpful. The authors use just the right amount of math to clarify the English text.