• Machine Learning

  • The Ultimate Guide to Machine Learning, Neural Networks and Deep Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More
  • By: Herbert Jones
  • Narrated by: Timothy Burke, Sam Slydell
  • Length: 7 hrs and 39 mins
  • Unabridged Audiobook
  • Release date: 11-05-18
  • Language: English
  • Publisher: Herbert Jones
  • 4.5 out of 5 stars (29 ratings)

Regular price: $19.95

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Publisher's Summary

Three comprehensive manuscripts in one audiobook.

  • Machine Learning: An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More
  • Neural Networks: An Essential Beginners Guide to Artificial Neural Networks and Their Role in Machine Learning and Artificial Intelligence
  • Deep Learning: An Essential Guide to Deep Learning for Beginners Who Want to Understand How Deep Neural Networks Work and Relate to Machine Learning and Artificial Intelligence

Here are some of the topics that are discussed in part one of this audiobook:

  • What is machine learning?
  • What’s the point of machine learning?
  • History of machine learning
  • Neural networks
  • Matching the human brain
  • Artificial intelligence
  • AI in literature
  • Talking, walking robots
  • Self-driving cars
  • Personal voice-activated assistants
  • Data mining
  • Social networks
  • Big Data
  • Shadow profiles
  • Biometrics
  • Self-replicating machines
  • And much, much more!

Here are some of the topics that are discussed in part two of this audiobook:

  • Programming a smart(er) computer
  • Composition
  • Self-driving neural networks
  • Taking everyone’s job
  • Quantum leap in computing
  • Attacks on neural networks
  • Neural network war
  • Ghost in the machine
  • No backlash
  • And much, much more

Here are some of the topics that are discussed in part three of this audiobook:

  • Improving the scientific method
  • How it all started
  • Appeasing the rebellious spirits
  • Evolving the machine brain
  • The future of deep learning
  • Medicine with the help of a digital genie
  • And much, much more

So listen to this audiobook now if you want to learn more about machine learning!

©2018 Herbert Jones (P)2018 Herbert Jones

What members say

Average Customer Ratings

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  • Overall
    5 out of 5 stars
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Recommended!

This book is a nice follow on to introductory pattern recognition texts such as Duda and Hart, though it can be read without any prior pattern recognition knowledge. It provides a nice mix of theory and practical algorithms, illustrated with numerous examples. An essential element of your machine learning library!

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    4 out of 5 stars
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Good Narrator

The book provides a very illuminating counterpoint to other books that promote the Computational Learning Theory (COLT / kernels / large margins) viewpoint of modern machine learning. Many of the same techniques such as boosting and support vector machines are discussed, but are motivated in different ways. Appropriate regularization is seen as the key to avoiding overfitting with complex models, rather than margin maximization.

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Very Straight Forward

This book is a miracle of clarity and comprehensiveness. It presents a unified approach to state of the art machine learning techniques from a statistical perspective. The layout is logical and the level of math is appropriate for applications-oriented engineers and computer scientists, as well as theorists.

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I Would Recommend

I would recommend you Bishop's machine learning book as an alternative if you want to gain a deeper understanding of Bayesian techniques--that one is more readable as well.

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Excellent Book


The book is excellent if you want to use it as a reference and study machine learning by yourself. It's quite comprehensive and deep in areas in which authors are most familiar & famous (frequentist approach, ensemble techniques, maximum likelihood and its variations, lasso).

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Concise an d Compiling


There is no denying that this book is widely beloved, held in high regard, and referred to as the bible for machine learning.

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    4 out of 5 stars
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Loved It

The book explains details about math, statistics and machine learning, which is required someone with strong background in one of those fields. I like it and would recommend to my friends.

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Great Book


Great book on the fundamentals of machine learning. Get your sleeves rolled up and expect to dig into the math.

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Machine Lerning

Great book for stats student. Covers basic machine learning techniques. Grab this book, I recommend it.

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Very Clear


This book is clear and concise and using it with the website lectures makes the learning easy and if you are a statistician like me, it is great for the review

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  • Darzi Jesse
  • 11-09-18

My First Experience

This is indeed my first experience to listen to a book about machine learning and it is really good one. I would like to recommend this book.

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    4 out of 5 stars
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  • Sienna
  • 11-09-18

BEST OF ALL

Machine learning is not a simple topic to learn about but, this author has made it so. I loved it.

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  • J.Mohammad
  • 11-09-18

Got What I Actually Needed

An outstanding book! Several folks on here are complaining that the book is difficult to follow because of the mathematics. Well, I hate to break it to those folks, but machine learning IS hard! There’s a reason why the best data scientists and predictive modelers are mathematicians and statisticians.

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    5 out of 5 stars
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  • Luca
  • 11-09-18

Grab Grab Grab

This book is used by many machine learning courses. It is used in the Stanford grad program, which should give everyone enough understand of the authors targeted audience.

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    4 out of 5 stars
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  • H.Mohammad
  • 11-09-18

Very Informative

I have learned a lot from it and will continue to go through it to learn even more from it as it does tend to become more lucid the more I go through it.

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  • Riley Ronnie
  • 11-09-18

A Proper Guide

This book is innovative and fresh. It is an important contribution that will become a classic. The level is between intermediate and advanced. Good for an advanced special topics course for graduate students in statistics.

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    5 out of 5 stars
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  • Evie
  • 11-09-18

Great Piece Of Work

Data mining is a field developed by computer scientists but many of its crucial elements are imbedded in important and subtle statistical concepts. Statisticians can play an important role in the development of this field but as was the case with artificial intelligence, expert systems and neural networks the statistical research community has been slow to respond.

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    5 out of 5 stars
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  • Carter F
  • 11-09-18

Data Mining

The authors have put a lot of care into trying to condense a swath of material into a concise reference. A book providing all of the prerequisite material would be massive and this book's goal is not to teach the fundamentals of mathematics; rather teach the elements of statistical learning. For achieving that goal the book has earned the praise it is due.

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  • Rubi L
  • 11-09-18

Comprehensive One

If you are interested in learning Machine Learning or wish to strengthen your understanding, you might be tempted to acquire this book. However, I will urge you to postpone such an impulse after considering the following:

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  • RR
  • 11-09-18

Great Overview


This book reviews many machine learning and data mining techniques, I am very happy to have this book, it helps me a lot on my academic research.