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Machine Learning for Beginners

Algorithms, Decision Tree & Random Forest Introduction
Narrated by: Lukas Arnold
Length: 1 hr and 23 mins
Categories: Non-fiction, Technology
4 out of 5 stars (16 ratings)

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Summary

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.

What members say

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  • Overall
    4 out of 5 stars
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    4 out of 5 stars

helped me

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

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thank you

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

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must listen

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

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very informative

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.

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great overview

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

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Aweful. Are 5 star reviews fraudulent?

This is book does not deliver on any of the promises made in the synopsis.

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    3 out of 5 stars

Ok but not recommended for a novice. But of a waste of a credit

Narration intonation is not great and makes a hard topic much harder. Punctuation wasn’t really observed and overall this book is not for beginners trying to grasp ML it’s more like a rapid overview for people already pretty steeped in algo’s and mathematical modeling.

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WELL EXPLAINED

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.

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useful book

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

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machine learning

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.