Machine Learning for Kids
A Playful Introduction to Artificial Intelligence
$58.72
- Paperback
392 pages
- Release Date
30 March 2021
Summary
AI Made Easy with 13 Projects
Machine learning (ML) is a foundational component of artificial intelligence (AI). AI operates on the principle that computers can learn independently with your guidance.
Machine Learning for Kids offers a painless introduction to machine learning. Through this book and its accompanying Scratch-based website, you’ll discover the ease of integrating machine learning into your projects, even without prior coding knowledge.
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Book Details
| ISBN-13: | 9781718500563 |
|---|---|
| ISBN-10: | 1718500564 |
| Author: | Dale Lane |
| Publisher: | No Starch Press,US |
| Imprint: | No Starch Press,US |
| Format: | Paperback |
| Number of Pages: | 392 |
| Release Date: | 30 March 2021 |
| Weight: | 562g |
| Dimensions: | 235mm x 177mm |
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What They're Saying
Critics Review
“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
About The Author
Dale Lane
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 companion website for this book is now used in thousands of schools, and has received worldwide acclaim.
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