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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
Narrated by: Timothy Burke, Sam Slydell
Length: 7 hrs and 39 mins
4 out of 5 stars (46 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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    1 out of 5 stars
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    1 out of 5 stars

10% Technology 90% Why it’s bad

I purchased this book to learn about how AI, big data, data mining, etc. works. What I received was hours of technophobia and explanations of why no one should use the internet (and something about nano-bots destroying the world, I think), written in the form of a high school research paper.

While a section on ethics should be included in any literature about the use of technology, the title leads the buyer to believe that they will gain knowledge and understanding about the mechanics of AI - they will not.

I am thankful that Audible allowed me to return this book.

11 of 11 people found this review helpful

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    3 out of 5 stars
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Global Warming?

I am a bit shocked at the claim of “we don’t really know what causes global warming” towards the end. It’s factually untrue.

7 of 7 people found this review helpful

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    1 out of 5 stars
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Very shallow

I was excited about this book, but found it to be very shallow. I only listened to part I, and lost patience. It uses the same examples as many other books, but their discussion falls short. I will return this book.

3 of 3 people found this review helpful

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    3 out of 5 stars
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Just watch a dozen YouTube videos instead

Pretty low level and at times naive interpretations of covered topics. Facebook topics were decent.

1 of 1 people found this review helpful

  • Overall
    5 out of 5 stars

It is really informative

It gives you a lot of information about Machine Learning, neural networks, and deep learning. The audiobook also uses terms that are easy to understand. Great work!

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Repetitive

The information included in both books repeat, but I think it's great for someone who is interested.

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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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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.

1 of 2 people found this review helpful

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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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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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  • Palindrome Mordnilap
  • 01-10-19

Not a bad intro, but fairly superficial

Pretty good as an introductory overview, with a few interesting insights along the way. Not especially advanced and doesn't really explain how any of the stuff really works, so if you're looking for details, try elsewhere. This is more about applications of machine learning with a bit of futurology thrown in.

1 of 1 people found this review helpful

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    2 out of 5 stars
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  • JP
  • 02-02-19

fails the Turing test

No informational content that you couldn't get from general media articles. Gave up on the neural networks book as it sounded like the author didn't really know what a neutral network is.

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  • Milan Topalov
  • 01-27-19

It is as informative as The Sun tabloid

You will find out a few interesting facts, but the remaining 85% of the book is just pure speculation. Author sounds like he read a few books on the topic, as opposed to being an expert. Book title is misleading, probably for marketing reasons. Book is mainly about AI developments and big data. Having said that, it was not total waste of time, but was kinda fun. Just like The Sun tabloid.

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  • Thomas H.
  • 01-27-19

Misleading

I was hoping to learn something about machine learning but instead this book is a long series of unproven rants about privacy. The title is very misleading, the book very disappointing

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    1 out of 5 stars
  • Matthew clarke
  • 01-20-19

Repetitive, with little substance

All three authors repete the others statments. Most of what is said is conjecture. Alot of assumed correlation not factoring in the wider science.

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    4 out of 5 stars
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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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  • 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.