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  • Machine Learning

  • The Absolute Beginner’s Guide to Learn and Understand Machine Learning Effectively
  • By: Hein Smith
  • Narrated by: William Bahl
  • Length: 1 hr and 36 mins

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Publisher's Summary

Just about anyone with the slightest bit of interest in modern technology is looking to learn more about machine learning. This innovative new form of computer programming is the primary tool that makes it possible for a machine to perform a wide range of tasks for you that could range from recommending a good movie to driving you to work every day. 

No doubt, it is the tech of the future. But it is also a subject that can literally boggle the mind. If you’re not already deep into the terminology and techniques of this wildly exciting new industry, finding information on it written in basic layman’s terms can be tough.

Most of the audiobooks on the topic assume that you have at least a fundamental knowledge of the subject. If you’re interested in getting a better grasp at just how this new technology works and what it means for the masses then this is the audiobook for you. Here you will learn: 

  • What machine learning truly is 
  • What are neural networks 
  • How it applies to deep learning 
  • What are algorithms and how are they used 
  • And some of the many applications that machine learning is already using 
  • And much more 

Machine learning is becoming an increasingly powerful tool that will have an impact on every aspect of our lives in the future. So, whether you need to find good product recommendations to meet your needs, or you want to go all out and live in your own smart home, machine learning will be at the core of it. This audiobook will make it easier to grasp the concepts behind it and get you started on a path that leads to a very bright future.

If you’re ready to have a tool that breaks down this complex topic in simple language then this is your chance. Download your copy now, so you can get started on what is promising to be a most amazing future. 

Don’t waste your time working with an audio guide that will only going to make an already complicated topic even more complicated. Scroll up and click the "Buy Now" button to learn everything you need to know in no time!  

©2018 HEIN SMITH (P)2018 SJ PUBLISHING

What listeners say about Machine Learning

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Profile Image for Larry Peterson
  • Larry Peterson
  • 24-01-2021

Very well-written book

Very well written book with a complete source code of a working neural network built step by step through the book. It takes the reader through building a real, working neural network without any required prior knowledge of complex math or any deep learning theory.

The theory and the inner workings of the NN are explained first in a very approachable way, then in the next part, the actual python program is being created, again in a very approachable and well-explained way.

My only regret is that it stops short of explaining some more advanced concepts like convolution layers, pooling layers, etc, that are found in modern neural networks for computer vision. Don't be put off by that though, it still explains A LOT of interesting and important concepts.

For someone like me who didn't have a clue how NN works only a month ago this book was the perfect eye-opener that gave me the foundations for future learning.

4 people found this helpful

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Profile Image for Marry Rose
  • Marry Rose
  • 31-12-2020

Comprehensive

Very well written book with a complete source code of a working neural network built step by step through the book. It takes the reader through building a real, working neural network without any required prior knowledge of complex math or any deep learning theory.
The theory and the inner workings of the NN are explained first in a very approachable way, then in the next part, the actual python program is being created, again in a very approachable and well-explained way.
My only regret is that it stops short of explaining some more advanced concepts like convolution layers, pooling layers, etc, that are found in modern neural networks for computer vision. Don't be put off by that though, it still explains A LOT of interesting and important concepts.
For someone like me who didn't have a clue how NN works only a month ago this book was the perfect eye-opener that gave me the foundations for future learning.

4 people found this helpful

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  • Susan Henderson
  • 29-12-2020

Really great

Machine Learning: The Absolute Beginner’s Guide to Learn and Understand Machine Learning Effectively by Hein Smith offers an in-depth introduction of what ML is all about. In each chapter you will learn the types of ML, supervised and unsupervised learning, the neural networks, how it all relates to deep learning, algorithms, machine learning applications, and the future of ML.

The book itself can be painful to work through, as it is written for a novice, not just in algorithms and data analysis, but also in programming. For the neural network aspect, it jumped between overly simplistic and complicated, while providing neither in enough detail. That said, by the end I found it a worthwhile dive into neural networks since once it got to the programming structure, it all made sense, but only because I stuck with it.

The author presented the core concepts of a simple neural network with a highly engaging style, taking the reader through each decision and clearly explaining the mathematics required with graphics a physical representation, and text.

4 people found this helpful

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    5 out of 5 stars
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    5 out of 5 stars
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  • Thea G.
  • 07-01-2021

Perfect guide

If you want to learn and understand Machine Learning effectively, then don't miss this guide. Machine learning is a subject that seems to be cropping up more and more these days - so if you're of a vaguely technical mind, why wouldn't you want to know more about it?

Smith's enthusiasm for the subject is very catching. It seems the book is aimed at people who understand a bit of maths and are reasonably computer-savvy. You don't have to be a programmer already - but it'd help. The book is a boon that saves the average reader from poring over endless, inscrutable academic texts to get into the subject - but at the same time, gives her or him the ability to maybe appreciate those texts afterward.

If you're new to the concepts or have never written a computer program before then this is likely to be hard work - but still totally doable - and very rewarding.

I utterly recommend this book to anyone who is new to and is interested in machine learning or computer programming.

3 people found this helpful

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    5 out of 5 stars
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  • Linda Price
  • 25-01-2021

Clearly written

Hein has written an excellent introduction to neural networks which takes you seamlessly from first principles through to a fully functional neural network with advanced optimization techniques. Clearly written and with useful examples peppered throughout, you will have a good understanding of what the neural network is doing whilst still achieving impressive prediction results. He also invites you to explore areas that can lead to further development and understanding but which would break the flow if included in the main text.

2 people found this helpful

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  • Kenneth Dee
  • 20-01-2021

Superb intro

Despite its title, this book provides a superb introduction to much of machine learning. Similarly, its treatment of Deep Learning is easily one of the best. The care with which the authors wrote is obvious, starting with systematically defining terms, a mark of true scholarship in my opinion. I can't over-recommend this book. And of course, the authors are all deeply involved (no pun intended) in developing Deep Learning in the first place. It doesn't get any better.

2 people found this helpful

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  • Franky
  • 19-01-2021

Great concept

Listening to this book makes me feel like I've worked on orders of magnitude more projects than I have. The examples are very clear and you're always left feeling like you understand why each topic is important. Not only did this book teach me new things about ML but it helped cement things I already figured out for myself on the job. More often than not, Hein's words are an invaluable reinforcement for concepts I thought I already knew.

2 people found this helpful

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  • Lorie
  • 16-01-2021

Helpful and interesting!

Fantastic book! I've been looking for a book that would take me through the basics of neural networks for some time. Usually, they either gloss over the important stuff so you don't really get to grips with the basics or they dive straight in and expect you to have a degree in higher maths.

This was perfect. The descriptions are clear and well-illustrated and the maths, although sometimes a bit tough, is also well explained.

The job now is to try and create a network of my own! But at least I feel that I could do it which is something that no other book has given me.

2 people found this helpful

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  • Mellorz David
  • 08-01-2021

Fantastic

Fantastic! Anyone looking to know more about machine learning will need an appropriate level of intelligence. But not all smart people can immediately grasp the concepts that comprise machine learning. This book enabled me to keep up with what was being communicated. Non-patronizing, clear, and informative. Thank you.

2 people found this helpful

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  • Maria Samson
  • 05-01-2021

Designed for absolute beginners

This book will break down the fundamentals of machine learning and what it truly means. You will get an overview of what it is about and what types of skills are required. For those with a deeper mathematical maturity, this book could also act as a good reference framework for all the different approaches and techniques covered. Overall, the book is really designed for absolute beginners as it explains in the title.

2 people found this helpful

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  • Sebastian
  • 31-12-2020

In-depth

If you want to learn and understand Machine Learning effectively, then don't miss this guide. Machine learning is a subject that seems to be cropping up more and more these days - so if you're of a vaguely technical mind, why wouldn't you want to know more about it?

Smith's enthusiasm for the subject is very catching. It seems the book is aimed at people who understand a bit of maths and are reasonably computer-savvy. You don't have to be a programmer already - but it'd help. The book is a boon that saves the average reader from poring over endless, inscrutable academic texts to get into the subject - but at the same time, gives her or him the ability to maybe appreciate those texts afterward.

If you're new to the concepts or have never written a computer program before then this is likely to be hard work - but still totally doable - and very rewarding.

I utterly recommend this book to anyone who is new to and is interested in machine learning or computer programming.

4 people found this helpful

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Profile Image for Carl James
  • Carl James
  • 24-01-2021

Thorough

Machine Learning: The Absolute Beginner’s Guide to Learn and Understand Machine Learning Effectively by Hein Smith offers an in-depth introduction of what ML is all about. In each chapter you will learn the types of ML, supervised and unsupervised learning, the neural networks, how it all relates to deep learning, algorithms, machine learning applications, and the future of ML.

The book itself can be painful to work through, as it is written for a novice, not just in algorithms and data analysis, but also in programming. For the neural network aspect, it jumped between overly simplistic and complicated, while providing neither in enough detail. That said, by the end I found it a worthwhile dive into neural networks since once it got to the programming structure, it all made sense, but only because I stuck with it.

The author presented the core concepts of a simple neural network with a highly engaging style, taking the reader through each decision and clearly explaining the mathematics required with graphics a physical representation, and text.

3 people found this helpful

  • Overall
    5 out of 5 stars
  • Performance
    5 out of 5 stars
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Profile Image for Jane Gates
  • Jane Gates
  • 19-01-2021

Excellent resource

If you are interested in Machine Learning, then this is an excellent resource for you. This is a well-explained introduction to the subject. 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. The author gives us information about what Machine Learning is and why it's important, a description of some of the most popular machine learning algorithms, and much more useful information. I find this book interesting and helpful. It is well written and easy to understand. I liked this guide very much. I got a lot of information on all my questions. I recommend this book to those in need of this type information

3 people found this helpful

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Profile Image for Chandrea
  • Chandrea
  • 16-01-2021

Such an informative book!

Very well written book with a complete source code of a working neural network built step by step through the book. It takes the reader through building a real, working neural network without any required prior knowledge of complex math or any deep learning theory.

The theory and the inner workings of the NN are explained first in a very approachable way, then in the next part, the actual python program is being created, again in a very approachable and well-explained way.

My only regret is that it stops short of explaining some more advanced concepts like convolution layers, pooling layers, etc, that are found in modern neural networks for computer vision. Don't be put off by that though, it still explains A LOT of interesting and important concepts.

For someone like me who didn't have a clue how NN works only a month ago this book was the perfect eye-opener that gave me the foundations for future learning.

3 people found this helpful

  • Overall
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Story
    5 out of 5 stars
Profile Image for Sol Lyn Sand
  • Sol Lyn Sand
  • 19-01-2021

Awesome

This book will break down the fundamentals of machine learning and what it truly means. You will get an overview of what it is about and what types of skills are required. For those with a deeper mathematical maturity, this book could also act as a good reference framework for all the different approaches and techniques covered. Overall, the book is really designed for absolute beginners as explains in the title.

2 people found this helpful

  • Overall
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Story
    5 out of 5 stars
Profile Image for Edward Thompson
  • Edward Thompson
  • 07-01-2021

Excellent

Fantastic book! I've been looking for a book that would take me through the basics of neural networks for some time. Usually, they either gloss over the important stuff so you don't really get to grips with the basics or they dive straight in and expect you to have a degree in higher maths.

This was perfect. The descriptions are clear and well-illustrated and the maths, although sometimes a bit tough, is also well explained.

The job now is to try and create a network of my own! But at least I feel that I could do it which is something that no other book has given me.

2 people found this helpful

  • Overall
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Story
    5 out of 5 stars
Profile Image for Sean Brown
  • Sean Brown
  • 29-12-2020

Awesome book

Are you intrigued by how people learn? Want to learn a bit about how the human brain has neurons that are connected to other neurons and in the process of sending signals between them, computation and learning take place?
Do you enjoy a bit of mathematics?
Do you appreciate authors who are able to take a complex subject and make it really easy to understand?
Have you ever dreamed about writing a program that can learn?
Have you ever wanted to write programs that weren’t just hacked together; rather, they were built upon solid mathematical principles?
Personally, I answer “yes” to all the above. (Although I am really rusty in mathematics).
This book, if read, accomplishes all the above. The book is on neural networks (a.k.a. deep learning). The book is fabulous. I cannot say enough good things about the book and the author. I knew nothing about neural networks prior to reading this book. As I said, my math skills are terribly rusty, but the author works through the math portions with tremendous patience. I am currently on page 92 and haven’t seen any programming stuff. Why? Because the author is first laying down the foundations. Then the programs will be built on top of solid concepts.
I highly, recommend this book.

2 people found this helpful

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    5 out of 5 stars
Profile Image for Devine Crawford
  • Devine Crawford
  • 10-01-2021

Fantastic

Most of the machine learning crash courses are way too long and I couldn't find any free quality material online. This book is not only affordable but it gives off a very simple introduction to machine learning that even people who have no experience with AI can understand. It is surprisingly meaty too talking about data sets and various machine learning techniques in later parts of the book. Even algorithm noobs can use this as a good place to get started.

1 person found this helpful

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    5 out of 5 stars
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    5 out of 5 stars
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    5 out of 5 stars
Profile Image for Lorie
  • Lorie
  • 09-01-2021

Superb introduction

Despite its title, this book provides a superb introduction to much of machine learning. Similarly, its treatment of Deep Learning is easily one of the best. The care with which the authors wrote is obvious, starting with systematically defining terms, a mark of true scholarship in my opinion. I can't over-recommend this book. And of course, the authors are all deeply involved (no pun intended) in developing Deep Learning in the first place. It doesn't get any better.

1 person found this helpful

  • Overall
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Story
    5 out of 5 stars
Profile Image for Bernard Go
  • Bernard Go
  • 07-01-2021

A splendid work

A splendid work, enormously useful for beginners to ML and all the way to pretty advanced readers; doesn't cover the most advanced concepts, but clearly explains where its coverage stops and offers very useful pointers to works in the vast ML literature. Thoroughly covers both the theory underlying various approaches (with as little advanced math as possible!) and many practical aspects of applying ML in real life, with good example data-sets

1 person found this helpful

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