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Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition) (AI, Data Science, Python & Statistics for Beginners) Kindle Edition

by O Theobald (Author) Format: Kindle Edition
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NOTICE: 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 Edition
This 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.

Disclaimer: 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 Learn:

• 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

Q: Do I need programming experience to complete this e-book?
A: 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.

Q: I have already purchased the First Edition of Machine Learning for Absolute Beginners, should I purchase this Second Edition?
A: As many of the topics from the First Edition are covered in the Second Edition, you may be better served reading a more advanced title on machine learning.

Q: Does this book include everything I need to become a machine learning expert?
A: Unfortunately, no. This book is designed for readers taking their first steps in machine learning and further learning will be required beyond this book to master machine learning.

Please feel welcome to join this introductory course by buying a copy, or sending a free sample to your device.
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  1. Part of series
    AI, Data Science, Python & Statistics for Beginners
  2. Print length
    168 pages
  3. Language
    English
  4. Publication date
    21 June 2017
  5. File size
    17098 KB
  6. Page Flip
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  7. Word Wise
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  8. Enhanced typesetting
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Total Kindle Price ₹976.00 + applicable tax
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  1. At an absolute minimum, a basic machine learning model should have ten times as many data points as the total number of features.
    Highlighted by 1,397 Kindle readers
  2. In machine learning, data is split into training data and test data.
    Highlighted by 1,058 Kindle readers
  3. You can find hundreds of interesting datasets in CSV format from kaggle.com.
    Highlighted by 1,029 Kindle readers
  4. Artificial intelligence, or AI, encompasses the ability of machines to perform intelligent and cognitive tasks.
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Product details

  • ASIN ‏ : ‎ B07335JNW1
  • Publisher ‏ : ‎ Scatterplot Press; 2nd edition (21 June 2017)
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 17098 KB
  • Text-to-Speech ‏ : ‎ Enabled
  • Screen Reader ‏ : ‎ Supported
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Print length ‏ : ‎ 168 pages
  • Customer Reviews:

About the authors

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  1. Oliver Theobald

    Oliver Theobald

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    Technical writer in the technology space for TikTok Business, Alibaba Cloud, and Ant Finance, now based in Japan.

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  2. O Theobald

    O Theobald

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Customer reviews

4.4 out of 5 stars
4.4 out of 5
1,508 global ratings

Top reviews from India

Ashish Majumdar
5.0 out of 5 stars Jump Starter
Reviewed in India on 12 July 2022
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This is a quick read. Touches basics of Machine Learning.
This book is highly recommended for non technical people who wants to understand and learn ML.
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Rajeev Raghunath
4.0 out of 5 stars Good Starter for Machine Learning
Reviewed in India on 3 October 2021
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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.
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Anshul Ranjan
5.0 out of 5 stars Very good book for a Novice
Reviewed in India on 6 January 2019
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The book organizes the theoretical and practical aspects of various ML techniques in very simple way which is great for a beginner. While this is not sufficient for anybody expecting to master the science, it's a great start to look further. The terminologies and basic concepts helps to set a direction to pursue for deeper learning. It also has good references for people looking to gain more expertise.
7 people found this helpful
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D.Kamalakannan
5.0 out of 5 stars Simple and understandable
Reviewed in India on 28 July 2020
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This book taught an overview of what is machine learning and how to create a model stage by stage. Also on how to use python for machine learning. Nice book helped me a lot.
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Deependu Ghosh
3.0 out of 5 stars Not Satisfied at all
Reviewed in India on 1 March 2020
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Too basic to cover such a vast topic.
2 people found this helpful
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Aditya Raj singh
5.0 out of 5 stars Nice
Reviewed in India on 17 April 2019
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Good and easy language
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Amazon Customer
4.0 out of 5 stars Simplified
Reviewed in India on 16 August 2018
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It's an simplified introduction to machine learning for beginners, it gives you fair idea of what , why and how of machine learning and ends with a practical example in python
One person found this helpful
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Yakub Pasha
5.0 out of 5 stars Best Beginners ML book
Reviewed in India on 25 October 2021
This is one of the best book I have read to understand Machine Learning concepts. To kick start your journey as Machine Learning practitioner, start from this book to understand basics of Machine Learning algorithm and how they work.
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Top reviews from other countries

Seaotter
5.0 out of 5 stars Great as a reference or review book
Reviewed in the United States on 5 February 2021
Verified Purchase
I found this book to be a great resource for reference, although I'm not sure it's for people completely lacking statistical or machine learning knowledge. The author references ML terms quite early on without really explaining what they are.

However, in my case, I was using this book to jog my memory of concepts I'd learned but forgotten in college. I majored in stats, with a focus in ML, then spent 2 years doing front end development. Now I'm going back to machine learning, and this book is the perfect, short and sweet summary of the terms and concepts needed to understand everything at a high level.

It's a great reference to have on your bookshelf - especially to remind yourself quickly or a term, or if you're trying to compare and decide on what algorithm you need to use for a new dataset.
3 people found this helpful
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Kyragos
5.0 out of 5 stars Does what is says
Reviewed in France on 1 June 2022
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As its title says, this is an introduction. A short, structured book useful for pure beginners in order to get a good grasp of data science, machine learning and the main algorithms. Obviously less useful for people with preexisting knowledge in machine learning. Prior basic knowledge of programming and mathematics is recommended.
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Dan C
5.0 out of 5 stars A valid introduction to machine learning
Reviewed in the United Kingdom on 11 April 2021
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I think this book does a really good job at explaining all the basic concepts of machine learning. I had started a Matlab course on ML at work for personal development but to be honest I hadn't taken the time to get an overview of the basic concepts written in clear understandable language. This does the job quite nicely. Some comments say that you can get all the information online... you could make thag comment about any knowledge base these days but thus is a well structured plain english book on machine learning that a pure beginner can sink their teeth into.
3 people found this helpful
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Robert
5.0 out of 5 stars A concise and easy to read introduction to machine learning
Reviewed in Canada on 14 February 2020
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Easy to understand as a novice and loved the fact that in the last couple of chapters, you actually get to put the book to use by building and optimising a decision tree based machine learning model using Python.
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Claire
5.0 out of 5 stars Great when you need a grasp of the basics quickly
Reviewed in Italy on 2 March 2021
Verified Purchase
An excellent book for beginners which explains machine learning terminology and concepts quickly. Great when you need a grasp of the basics quickly
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