Machine Learning for Kids: A Project-Based Introduction to Artificial Intelligence

by Dale Lane

Overview

A hands-on, application-based introduction to machine learning and artificial intelligence (AI). Create compelling AI-powered games and applications using the Scratch programming language.

AI Made Easy with 13 Projects

Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help.

Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based companion website, you’ll see how easy it is to add machine learning to your own projects. You don’t even need to know how to code!

Step by easy step, you’ll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve them.

You’ll turn your models into 13 fun computer games and apps, including:

A Rock, Paper, Scissors game that recognizes your hand shapes

A computer character that reacts to insults and compliments

An interactive virtual assistant (like Siri or Alexa)

A movie recommendation app

An AI version of Pac-Man

There’s no experience required and step-by-step instructions make sure that anyone can follow along!

No Experience Necessary! Ages 12+

Product Details

ISBN-13:	9781718500563
Publisher:	No Starch Press
Publication date:	02/09/2021
Pages:	392
Sales rank:	454,488
Product dimensions:	7.00(w) x 9.20(h) x 1.10(d)
Lexile:	1090L (what's this?)
Age Range:	12 - 14 Years

About the Author

Dale Lane is an award-winning, UK-based software developer for IBM, where he's worked on IBM's (AI) Watson platform since 2011. The father of two children, he's gained distinction working on projects and games that help explain core principles of machine learning to younger students. Lane's free companion website for this book (https://machinelearningforkids.co.uk/) is now used in thousands of schools, and has received worldwide acclaim.

Table of Contents

Foreword xv

Introduction xix

Scratch xx

Working in the Scratch Interface xxi

Coding in Scratch xxii

Saving Your Work xxiv

Machine Learning for Kids xxiv

What's Next? xxiv

1 What Is Artificial Intelligence? 1

Coding 2

Machine Learning 3

Artificial Intelligence 3

Neural Networks and Deep Learning 4

What You Learned 5

2 Introducing Machine Learning for Kids 7

Logging In 8

Creating a New ML Project 9

Phases of an ML Project 11

Train 11

Learn & Test 12

Make 13

Creating an Account 14

What You Learned 17

3 Sorting Animal Pictures 19

Build Your Project 20

Train Your Model 21

Prepare Your Project 26

Test Your Model 31

Review and Improve Your Project 32

What You Learned 35

4 Playing Rock, Paper, Scissors Against Your Computer 37

Build Your Project 38

Train Your Model 38

Prepare Your Game 42

Test Your Game 45

Review and Improve Your Project 46

What You Learned 48

5 Recognizing Movie Posters 49

Build Your Project 51

Train Your Model 52

Prepare Your Model 56

Test Your Model 65

Review and Improve Your Project 65

What You Learned 66

6 Mail Sorting 67

Build Your Project 69

Train Your Model 69

Prepare Your Project 74

Test Your Project 81

Review and Improve Your Project 82

What You Learned 82

7 Insulting a Computer 83

Build Your Project 85

Prepare Your Game 85

Code Your Game Without ML 88

Train Your Model 90

Code Your Game with ML 94

Test Your Game 96

Review and Improve Your Project 96

Using Speech Input Instead of Typing 96

Recognizing Speech That Isn't a Compliment or Insult 97

Learning from Mistakes 99

What You Learned 100

8 Recognizing Language in Newspapers 103

Build Your Project 104

Train Your Model 106

Prepare Your Project 110

Review and Improve Your Project 118

Measuring Performance: Accuracy 118

Measuring Performance: Confusion Matrix 121

Measuring Performance: Precision and Recall 126

Improving Your ML Model 127

What You Learned 128

9 Finding an Object in a Picture 129

Build Your Project 132

Train Your Model 132

Prepare Your Project 140

Test Your Project 142

Review and Improve Your Project 143

Real-World Applications for Complex Image Recognition Systems 145

What You Learned 149

10 Smart Assistants 151

Build Your Project 153

Code Your Project Without ML 153

Train Your Model 155

Code Your Project with ML 159

Test Your Project 161

Review and Improve Your Project 161

Using Your Model's Confidence Score 161

Using Speech Input Instead of Typing 163

Collecting Training Data 164

What Your Learned 165

11 Chatbots 167

Build Your Project 169

Prepare Your Character 170

Train Your Model 171

Prepare Your Project 176

Test Your Project 177

Review and Improve Your Project 177

Responding and Recording When Users Report Mistakes 178

Recognizing When a User Isn't Happy 180

Answering Only When the ML Model Is Confident 180

ML and Ethics 182

What You Learned 182

12 Avoiding the Monster 185

Build Your Project 187

Describe the State of the Game 188

Train Your Model 189

Test Your Game 197

Review and Improve Your Project 200

What You Learned 202

13 Tic Tac Toe 203

Build Your Project 205

Prepare Your Game 208

Train Your Model 217

Test Your Game 219

Review and Improve Your Project 221

What You Learned 221

14 Confusing the Computer 223

Build Your Project 225

Train Your Model 227

Prepare Your Project 230

Test Your Project 232

Review and Fix Your Project 233

What You Learned 236

15 Biasing the Computer 237

Build Your Project 238

Train Your Model 238

Prepare Your Project 241

Test Your Project 244

Introduce Bias 244

Test Your Biased Project 246

Review Your Project 247

The Case for Bias 248

AI and Ethics 248

What You Learned 250

Afterword 251

The Future 252

Next Steps 252

Index 255

Editorial Reviews

"Machine Learning for Kids is another leading-edge resource for data scientists, this time for very young data scientists."
—Daniel Gutierrez, insideBIGDATA

“What delights me about this book is that it’s wonderfully pragmatic, for it guides you in building AI systems that are very much relevant to contemporary computer science.” (from the foreword)
—Grady Booch, IBM Fellow and Chief Scientist for Software Engineering, IBM Research

"The book is a guided hands-on and practical introduction to how artificial intelligence impacts our lives. It includes step-by-step instructions for making a variety of machine learning-powered projects in Scratch, and explains how they each relate to real-world AI applications."
—Alphonse Devasia Blog

"Machine Learning and children in one sentence is only possible when cool folks like Dale Lane make it their passion to ‘make tech understandable.'"
—Coding and More, YouTuber

From the Publisher