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Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition)
To buy the newest edition of this book (2021), please search "Machine Learning Absolute Beginners Third Edition" on Amazon. The product page you are currently viewing is for the 2nd Edition (2017) of this book.Featured by Tableau as the first of "7 Books About Machine Learning for Beginners."Ready to spin up a virtual GPU instance and smash through petabytes of data? Want to add 'Machine Learning' to your LinkedIn profile?Well, hold on there...Before you embark on your epic journey, there are some high-level theory and statistical principles to weave through first.But rather than spend $30-$50 USD on a dense long textbook, you may want to read this book first. As a clear and concise alternative to a textbook, this book provides a practical and high-level introduction to machine learning.Machine Learning for Absolute Beginners Second Edition has been written and designed for absolute beginners. This means plain English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home.New Updated EditionThis major new edition features many topics not covered in the First Edition, including Cross Validation, Ensemble Modeling, Grid Search, Feature Engineering, and One-hot Encoding. Please note that this book is not a sequel to the First Edition but rather a restructured and revamped version of the First Edition. Readers of the First Edition should not feel compelled to purchase this Second Edition. If you have passed the 'beginner' stage in your study of machine learning and are ready to tackle coding and deep learning, you would be well served with a long-format textbook. If, however, you are yet to reach that Lion King moment - as a fully grown Simba looking over the Pride Lands of Africa - then this is the book to gently hoist you up and offer you a clear lay of the land.
In This Step-By-Step Guide You Will � How to download free datasets� Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data� Preparing data for analysis, including k-fold Validation� Regression analysis to create trend lines� Clustering, including k-means clustering, to find new relationships� The basics of Neural Networks� Bias/Variance to improve your machine learning model� Decision Trees to decode classification� How to build your first Machine Learning Model to predict house values using Python
Frequently Asked Questions Do I need programming experience to complete this e-book? This e-book is designed for absolute beginners, so no programming experience is required. However, two of the later chapters introduce Python to demonstrate an actual machine learning model, so you will see programming language used in this book.
In This Step-By-Step Guide You Will � How to download free datasets� Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data� Preparing data for analysis, including k-fold Validation� Regression analysis to create trend lines� Clustering, including k-means clustering, to find new relationships� The basics of Neural Networks� Bias/Variance to improve your machine learning model� Decision Trees to decode classification� How to build your first Machine Learning Model to predict house values using Python
Frequently Asked Questions Do I need programming experience to complete this e-book? This e-book is designed for absolute beginners, so no programming experience is required. However, two of the later chapters introduce Python to demonstrate an actual machine learning model, so you will see programming language used in this book.
168 pages, Kindle Edition
Published June 21, 2017
1,946 people are currently reading
666 people want to read
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Displaying 1 - 21 of 21 reviews
March 4, 2019
Fill in Those Missing Gaps
If you find yourself questioning terms and approaches while taking a machine learning course then this is the book that will help filling in those details.
If you find yourself questioning terms and approaches while taking a machine learning course then this is the book that will help filling in those details.
May 28, 2019
I have to admit: this a great book to break the ice, machine learning is a well-known highly difficult topic and there aren’t many introductory books! The author did a good job putting all the key concepts together into such a short book.
October 4, 2024
This was a short but effective read. It gives a good overview of machine learning algorithms without getting too bogged down in the minutia.
There is a "Bug Bounty" where you can email the author about bugs. I emailed three in, but haven't heard anything back. We'll see if it pans out.
There is a "Bug Bounty" where you can email the author about bugs. I emailed three in, but haven't heard anything back. We'll see if it pans out.
June 9, 2019
Super helpful
Overall very well paced. Great book to get a overarching view of machine learning. Simple language through out to explain some of the complex concepts. I thoroughly enjoyed reading.
Overall very well paced. Great book to get a overarching view of machine learning. Simple language through out to explain some of the complex concepts. I thoroughly enjoyed reading.
December 13, 2020
I decided to have a crack at a machine learning project for a hackday project at work as an excuse to get a crash course in ML. There is a wealth of freely available resources online but it's such a broad topic it's hard to know where to focus. Then I stumbled across this book so gave it a crack and it was perfect for my need. Covered broadly some of the key concepts of ML in a reasonable sized and paced book that you can get through pretty quickly, and finishes with some code walkthroughs as a perfect stepping stone to exploring on your own.
This book is limited to beginners, so it doesn't go into depth and probably skips over a lot of areas that you may need to dig into if you want to get serious about ML. However, as an introduction for beginners where you need more holistic coverage than articles/blogs online this is a great start.
If you are interested in getting into ML or just want a bit more understanding of what it involves this is a great read, an easy 5/5 since it achieves exactly what it sets out to do.
This book is limited to beginners, so it doesn't go into depth and probably skips over a lot of areas that you may need to dig into if you want to get serious about ML. However, as an introduction for beginners where you need more holistic coverage than articles/blogs online this is a great start.
If you are interested in getting into ML or just want a bit more understanding of what it involves this is a great read, an easy 5/5 since it achieves exactly what it sets out to do.
May 27, 2024
This book is a fantastic starting point for anyone curious about machine learning but overwhelmed by the technical jargon. Written in plain English, it demystifies complex concepts and presents them in an easy-to-understand manner. The author breaks down the fundamentals, providing clear explanations and practical examples that make the material accessible even to those with no prior knowledge. What sets this book apart is its hands-on approach. Each chapter includes exercises and projects that reinforce learning and allow readers to apply what they've learned immediately. The gradual progression from basic to more advanced topics ensures that readers build a strong foundation before moving on to more complex subjects. Overall, this book is an excellent resource for absolute beginners looking to dive into the world of machine learning. Its straightforward language, practical examples, and engaging projects make it an invaluable guide for anyone eager to learn.
March 18, 2020
Good introduction to machine learning
I liked the range of topics and examples that were described but some concepts, especially the types of algorithms, still seemed a little advanced for an “absolute beginners� book. For me, I had to read some sections multiple times to grasp the concept.
I did like the last couple of chapters that showed how to work with a dataset to run through a machine learning problem. It was written well with good step by step procedures.
I liked the range of topics and examples that were described but some concepts, especially the types of algorithms, still seemed a little advanced for an “absolute beginners� book. For me, I had to read some sections multiple times to grasp the concept.
I did like the last couple of chapters that showed how to work with a dataset to run through a machine learning problem. It was written well with good step by step procedures.
October 3, 2021
Good Starter for Machine Learning
The world is now behind Machine Learning, to ease up and provide better facility and thereby improving the capabilities on our the day to day actions. This is a good place to start the journey into this new world. I would say understanding ML is a must as it is invading every nook and corner of the streams available in our realm. So start your journey and for that this is a good Starter.
The world is now behind Machine Learning, to ease up and provide better facility and thereby improving the capabilities on our the day to day actions. This is a good place to start the journey into this new world. I would say understanding ML is a must as it is invading every nook and corner of the streams available in our realm. So start your journey and for that this is a good Starter.
March 31, 2024
3.5 stars rounded down.
Decent introduction to machine learning. An area which I have been interested in for quite a while.
However, this does get a little confusing at times. Especially when it becomes quite technical, into the second half.
An extra star for the additional resources.
Regardless, engaging read.
Decent introduction to machine learning. An area which I have been interested in for quite a while.
However, this does get a little confusing at times. Especially when it becomes quite technical, into the second half.
An extra star for the additional resources.
Regardless, engaging read.
August 29, 2017
I found this to be a very nice roundup on this important and developing topic. The erratic editing was distracting starting with the sub-title ("beginner's" - plural not possessive, no apostrophe!), and kept me from giving a higher rating.
September 6, 2018
Awesome book
This book has helped in clearing up some of my obviousness to machine learning. However, the chapter on decision trees and gradient boosting needs some more content. Nevertheless, awesome book
This book has helped in clearing up some of my obviousness to machine learning. However, the chapter on decision trees and gradient boosting needs some more content. Nevertheless, awesome book
March 31, 2018
Very good overview
Excellent overview for someone just starting to learn about ML. Covers the basics and a good introduction to the terms used in M
.
Excellent overview for someone just starting to learn about ML. Covers the basics and a good introduction to the terms used in M
.
August 29, 2018
Great intro to ML
Great book for newbies to machine learning. You will get more from the book if you have a some knowledge of python.
Great book for newbies to machine learning. You will get more from the book if you have a some knowledge of python.
January 10, 2019
Really good overview
Simple to understand and a great starting point for ML. I am now ready for much more advanced ML stuff.
Simple to understand and a great starting point for ML. I am now ready for much more advanced ML stuff.
February 1, 2019
It does it’s job and explains machine learning to a non-computer scientist. If that’s your goal it’s worth the read.
March 1, 2020
The book is well structured and starts with the basics. The details are enough so you understand the concepts and allow you to follow the conversation in a meeting.
June 22, 2020
Good high level summary
Provides a quick overview of the key concepts. Though you would still need to get some hands on exercise outside of this to fully grasp the main ideas.
Provides a quick overview of the key concepts. Though you would still need to get some hands on exercise outside of this to fully grasp the main ideas.
July 25, 2021
Review
The book is ok for review of basic AIML. I found the book bit more technical for beginners as opposed to focusing on the basics.
The book is ok for review of basic AIML. I found the book bit more technical for beginners as opposed to focusing on the basics.
August 17, 2023
A quick read for beginners for introductory machine learning and it tells us the basic concept of different machine learning methods but t spares us from complex maths
April 22, 2018
The perfect intro
A great intro to the topic with hands on application and suggestions for further learning. Thank you for writing this book
A great intro to the topic with hands on application and suggestions for further learning. Thank you for writing this book
May 3, 2018
Great introduction
I will need a second pass on the book but I think it gave a great introduction to the world of machine learning. Not boring at all!
I will need a second pass on the book but I think it gave a great introduction to the world of machine learning. Not boring at all!
Displaying 1 - 21 of 21 reviews
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