Machine Learning for Kids: A Project-Based Introduction to Artificial Intelligence
內容描述
A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. 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, award-winning 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 As you work through the book 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 their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: - Rock, Paper, Scissors game that recognizes your hand shapes - An app that recommends movies based on other movies that you like - A computer character that reacts to insults and compliments - An interactive virtual assistant (like Siri or Alexa) that obeys commands - An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+
作者介紹
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.
