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Machine Learning for Beginners

Algorithms, Decision Tree & Random Forest Introduction

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Machine Learning for Beginners

By: William Sullivan
Narrated by: Lukas Arnold
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About this listen

Machines can learn?!

Machine learning occurs primarily through the use of "algorithms" and other elaborate procedures.

Whether you're a novice, intermediate, or expert this book will teach you all the ins, outs and everything you need to know about machine learning.

Instead of spending hundreds or even thousands of dollars on courses/materials why not listen to this audiobook instead? It's a worthwhile listen and the most valuable investment you can make for yourself.

What you'll learn:

  • Supervised learning
  • Unsupervised learning
  • Reinforced learning
  • Algorithms
  • Decision tree
  • Random forest
  • Neural networks
  • Python
  • Deep learning
  • And much, much more!

This is the most comprehensive and easy step-by-step guide in machine learning that exists.

Learn from one of the most reliable programmers alive and expert in the field.

©2017 Healthy Pragmatic Solutions Inc. (P)2017 Healthy Pragmatic Solutions Inc. Computer Science Engineering Machine Theory & Artificial Intelligence Programming & Software Development Software Development Machine Learning Data Science Programming Artificial Intelligence Software

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All stars
Most relevant  
I've been curious about this subject for a while and recently started to do some research. This book provided a nice high-level understanding of the topic and it's related subject matter.

very informative

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This is a fantastic book for the absolute beginner. Although extremely elementary in content, it is very useful for someone with no background

great overview

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The title says it all. I have been introduced to ML as an absolute beginner. Great examples and easy . Thank you

thank you

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Highly visual and easy to follow
I'd strongly recommend this book. What I liked about it were the visual explanations of algorithms and the practical explanation of k-means clustering, PCA and linear regression. There's not the same detailed guide for the chapter on neutral networks which was a shame. but it is an absolute beginner's book after all.

WELL EXPLAINED

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Technical enough to make me feel like I was learning things but broad enough to let me read through the book without any hiccups

must listen

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The book is a perfect guide to learn about the Machine learning. I get this book to upgrade my self so I found that this is a big value addition in my career thanks.

nice book

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As a beginner I felt the pace of the book was very manageable and each concept is well explained with clear points, often backed up with visual illustrations. You get a good context on what is ML, the algorithms that power ML, and guidance on further learning careers. This book is not a substitute for a textbook but would be a nice complementary resource for anyone starting out in this subject. I feel that business folks or journalists who don’t have a lot of time to sit down and learn this advanced field and who need a rapid snapshot of ML would do well to this book. As a title geared to ‘absolute beginners’, I would not recommend to more advanced stage learners to this book. For me though it hit the spot. Would look forward to a second title in this series if there is one.

machine learning

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This is a good and quick listen into the popular algos in Data Science. As the title suggests, it is a good intro and offers several resources to dive into the world of Data Science

helped me

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The book is short but I think that's it's strong suit. I suspect it's usefulness will wear off as this information becomes more foundational knowledge through my research into ML but as a beginner in the field, I find that having an easy to navigate reference book for the algorithms I need to learn to become an ML expert is very useful

useful book

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This is a very interesting and useful book. In it you can learn about automatic science for beginners. I advise this book, it has a lot of different and travel information.

Interesting book....

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