Machine Learning for Absolute Beginners: A Plain English Introduction (Third Edition): 3 (Python for Data Science)

(Featured and recommended by Tableau as the first of "7 Books About Machine Learning for Beginners")

Want to add 'Machine Learning with Python' to your LinkedIn profile and spin up a real estate prediction model?

Well, hold on there...

Before you embark on your journey, there are some high-level theory and statistical principles to weave through first.
However, rather than spend $30-$50 USD on a thick textbook, you may want to read this book first.

As a clear and concise alternative, this book provides a step-by-step introduction to machine learning concepts 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 to follow along.

New Updated Edition
This new edition features extended chapters with quizzes, free supplementary online video tutorials for coding models in Python, an easy introduction to coding with Python, and other downloadable resources not included in the Second Edition.

Disclaimer: If you have passed the 'beginner' stage in your study of machine learning and are ready to tackle coding exercises and deep learning, you would be better served by other books on machine learning. If, though, 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 machine learning book to gently hoist you up and give you a clear lay of the land.

In this step-by-step guide you will learn:

• How to download free datasets
• What tools and machine learning libraries to use
• 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
• 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, and
• How to build your first model to predict house values using Python for machine learning

Frequently Asked Questions

Q: Do I need programming experience to complete this book?
A: This book is designed for absolute beginners, so no programming experience is required. However, two of the later chapters introduce machine learning with Python to demonstrate an actual prediction model, so you will see some code used in this book.

Q: I have already purchased the Second Edition of Machine Learning for Absolute Beginners, should I purchase this Third Edition?
A: As the same topics from the Second Edition are covered in the Third Edition, you would be better served by reading a more advanced book on machine learning and AI. If you have purchased a previous edition of this book and wish to get access to the free video tutorials, please email the author.

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 AI, and further learning will be required beyond this book to master AI/machine learning and become the next Andrew Ng.