The Ultimate Guide to Machine Learning For Absolute Beginners: Learn the Future of Technology

Welcome to the exciting world of machine learning! In this comprehensive guide, we will unravel the mysteries of this revolutionary technology and walk you through the fundamentals of machine learning algorithms, applications, and how they shape the future.

Chapter 1: to Machine Learning

Machine learning is the science of creating algorithms that can learn and make predictions or decisions without being explicitly programmed. It mimics the way humans learn, adapting and improving from experience. Discover how machine learning is transforming various industries, from healthcare to finance, and how it works hand in hand with artificial intelligence.

Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition) (Machine Learning From Scratch Book 1)

by O Theobald (Kindle Edition)

4.5 out of 5

Language	:	English
File size	:	17512 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	164 pages
Lending	:	Enabled
Paperback	:	44 pages
Item Weight	:	2.39 ounces
Dimensions	:	6 x 0.11 x 9 inches

FREE

Chapter 2: Types of Machine Learning Algorithms

We'll explore the different types of machine learning algorithms, including supervised, unsupervised, and reinforcement learning. Uncover the inner workings of these algorithms as we delve into classification, regression, clustering, and anomaly detection. Understand the strengths and weaknesses of each algorithm and how to choose the right one for your specific problem.

Chapter 3: Data Preprocessing and Feature Engineering

Data preprocessing is a crucial step in machine learning. Discover how to clean, transform, and prepare your data for analysis. Learn the art of feature engineering, where we extract the most relevant information from our data to improve model accuracy.

Chapter 4: Model Selection and Evaluation

Not all models are created equal. In Chapter 4, we'll guide you through the process of selecting the appropriate model for your problem. Learn about common evaluation metrics and techniques to assess model performance. Dive into concepts such as overfitting and underfitting and explore how to avoid these issues to build robust and accurate models.

Chapter 5: Machine Learning in Action

Now it's time to put your knowledge to work! In this chapter, we'll provide practical examples of machine learning projects across different industries. From predicting customer churn to image recognition, you'll see how machine learning is transforming businesses and driving innovation.

Chapter 6: Future of Machine Learning

As machine learning continues to evolve at a rapid pace, we'll explore the future of this technology. Discover the emerging trends, challenges, and opportunities that lie ahead. Gain insights into the ethical considerations of machine learning and understand its potential impact on society.

Machine learning opens up a world of possibilities. Whether you're a novice or a seasoned professional, this guide will equip you with the fundamental knowledge and skills to dive into the exciting field of machine learning. Get ready to unleash your creativity and explore the limitless potential of this future-forward technology. Start your journey today!

Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition) (Machine Learning From Scratch Book 1)

by O Theobald (Kindle Edition)

4.5 out of 5

Language	:	English
File size	:	17512 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	164 pages
Lending	:	Enabled
Paperback	:	44 pages
Item Weight	:	2.39 ounces
Dimensions	:	6 x 0.11 x 9 inches

FREE

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 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.