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Machine Learning

An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More
Lu par : Timothy Burke
Durée : 2 h et 4 min
5 out of 5 stars (1 notation)

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Description

If you're at the beginner's stage and are looking to gain new knowledge about machine learning, then keep reading....

Do not listen to this audiobook if you're looking for a boring textbook containing a lot of dry math and programming lingo.

Every day, someone is giving up on learning about machine learning. Many people miss out on furthering their career, and perhaps even the progress of our species without even realizing

You see, most beginners make the same mistakes when first delving into the topic of machine learning. They start off with a resource containing too many unrelatable facts, math, and programming lingo that will put them to sleep rather than ignite their passion.

But that is all about to change.

This new book on machine learning will explain the concepts, methods, and history behind machine learning, including how our computers became vastly more powerful but infinitely less intelligent than ever before and why every tech company and their grandmother want to keep track of us 24/7, siphoning data points from our electronic devices to be crunched by their programs that then try to become virtual crystal balls, predicting our thoughts before we even have them. 

Most of the book seems like science-fiction because, in a sense, it is, far beyond what an average person would be willing to believe is happening. 

Here are some of the topics that are discussed in this book:

  • What machine learning is
  • What the point of machine learning is
  • 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
  • And much more!

Listen now to learn more!

©2018 Herbert Jones (P)2018 Herbert Jones
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Notations
Global
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  • Global
    5 out of 5 stars

Reminder

This book reminds AI designers to be careful when producing software. Like all tools, AI, though fascinating, needs guidelines.

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  • Global
    1 out of 5 stars
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Image de profile pour navarro
  • navarro
  • 29/12/2019

Use case

To generic exemple. We are missing the more precise use case and benefits in this book.

  • Global
    5 out of 5 stars
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Image de profile pour Hanna Macleod
  • Hanna Macleod
  • 08/09/2018

A best and easy way to learn.

I was in search for a good and easy book and one of the my friend told me about this one and he also send me a promo for this book as well. I got it very nice and easy book. There is much information about learning the Machine Learning.

  • Global
    3 out of 5 stars
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    3 out of 5 stars
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Image de profile pour Marcos Lacerda
  • Marcos Lacerda
  • 31/08/2018

Nothing new, no insights

No insights if you follow the news about the subject. A bit more superficial than what I was expecting.

  • Global
    5 out of 5 stars
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Image de profile pour Linda Cherylh
  • Linda Cherylh
  • 28/08/2018

A great experienced author about ML.

Generally, I am very satisfied with this book. Beforehand I have been speechless with the math and this helped draw me back out a few steps to better understand the concepts.

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Image de profile pour Bradley  Kimbrell
  • Bradley Kimbrell
  • 28/08/2018

Excellent getting started book.

I enjoyed the listen-ability of this book. The emphasis is on how to use and understand Machine Learning rather than the math behind the algorithms. Was an enjoyable read.

  • Global
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Image de profile pour Razan Diraf
  • Razan Diraf
  • 28/08/2018

its a decent ML boook.

The author seems a senior developer who has good information about Machine Learning concepts in the past despite a strong math background as well. I was optimistic that a book for total laities would help, but as someone who learns mainly by doing, the tips are easy to follow.

  • Global
    5 out of 5 stars
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Image de profile pour Shirley Perine
  • Shirley Perine
  • 28/08/2018

Its good book, good informative stuff.

I found it just wasn't hands-on enough. The information was good, but the lack of worked examples or exercises left me feeling like I hadn't learned all that much. I'd say if you're someone who can read information and absorb it, this could be a great introduction to the subject. But if you're like me and need a sandbox, you might want to keep looking.

  • Global
    5 out of 5 stars
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Image de profile pour Jason T. Chen
  • Jason T. Chen
  • 28/08/2018

The perfect intro to learn ML.

This is a great intro to the topic with hands on application and proposals for additional learning. Thank you for writing this book, the author has the command.

  • Global
    5 out of 5 stars
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Image de profile pour John M. Depasquale
  • John M. Depasquale
  • 28/08/2018

The book is also quite practical.

This book is ideal for people first coming into Machine Learning looking for a clear high-level introduction. Having said that, the book is also quite practical too, and I had good fun going through the example exercises to build regression lines and scrub data-sets.

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Image de profile pour Michael C. Walker
  • Michael C. Walker
  • 26/08/2018

A Good Introduction for Beginners.

This book is perfect for people first coming into Machine Learning looking for a clear high-level introduction. Having said that, the book is also quite practical too, and I had good fun going through the example exercises to build regression lines and scrub datasets.

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  • Global
    1 out of 5 stars
  • Interprétation
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Image de profile pour "ahermle"
  • "ahermle"
  • 24/12/2018

Old-fashioned

Book seems to have been written before 1970. Quote "self driving cars ..... they are unlikely to appear within the next 50 years". BMW just announced the first self driving car produced in series production for 2021.