The Mathematics of Artificial Intelligence for High Schoolers - Couverture souple

Wilmott, Paul

Couverture souple

ISBN 10 : 1916081649 ISBN 13 : 9781916081642

Editeur : Panda Ohana Publishing, 2023

Synopsis

This is the book that introduces schoolchildren to the mathematics behind Artificial Intelligence.

2023 Royal Dragonfly Book Award Honorable Mention!

There are books with no mathematics, just the description of what AI can do. Then there are books with no mathematics, just lots of computer code. And there are books with lots and lots of mathematics which are incomprehensible without a degree in mathematics.

But there aren't books like this one!

This book is for children who are confident in their mathematics. They do not have to be advanced or even top of their class. But they do have to be comfortable with learning new concepts. Here are some of those concepts, and how simple they are.

• Representing data as a vector: A list of numbers, don't be fooled by the big parentheses!
• Scaling the data: Taking away and multiplying. That was easy!
• Distance measurement: Taking away and adding up. Squaring and square rooting if you are feeling really adventurous!
• Charts: Putting dots on a piece of graph paper! Exhausted, not!
• The equation of a straight line: y = ax+b. You can do it!
• Averages: Adding up and dividing. You know how to divide, don't you, Steve?

Yes, it's mathematics, but nothing to frighten the horses!

The book starts with a chapter with some history of AI. This is followed by a chapter of jargon, useful mathematics, and a description of the main techniques. Then it's one chapter on each of Nearest Neighbours, Regression, Clustering, Decision Trees, Neural Networks and Reinforcement Learning. Each of these in-depth chapters covers uses of the technique, the mathematical details, a real example and then a project for readers to work through on their own or in teams. The book ends with sources for some useful data.

A propos du livre

À propos de l'auteur

Paul Wilmott studied mathematics at St Catherine's College, Oxford, where he also received his D.Phil. He is the author of Paul Wilmott Introduces Quantitative Finance (Wiley 2007), Paul Wilmott On Quantitative Finance (Wiley 2006), Frequently Asked Questions in Quantitative Finance (Wiley 2009), The Money Formula (with David Orrell) (Wiley 2017) and other financial textbooks. He has written over 100 research articles on finance and mathematics. Paul Wilmott was a founding partner of the volatility arbitrage hedge fund Caissa Capital which managed $170 million. His responsibilities included forecasting, derivatives pricing, and risk management. Paul is the proprietor of www.wilmott.com, the popular quantitative finance community website, and the quant magazine Wilmott. He is the creator of the Certificate in Quantitative Finance, cqf.com, and the President of the CQF Institute, cqfinstitute.org. Paul Wilmott has been called "cult derivatives lecturer" by the Financial Times and "financial mathematics guru" by the BBC.

À propos de la quatrième de couverture

This is the book that introduces schoolchildren to the mathematics behind Artificial Intelligence! There are books with no mathematics, just the description of what AI can do. Then there are books with no mathematics, just lots of computer code. And there are books with lots and lots of mathematics which are incomprehensible without a degree in mathematics. But there aren't books like this one! This book is for children who are confident in their mathematics. They do not have to be advanced or even top of their class. But they do have to be comfortable with learning new concepts. Here are some of those concepts, and how simple they are. Representing data as a vector: A list of numbers, don't be fooled by the big parentheses! Scaling the data: Taking away and multiplying. That was easy! Distance measurement: Taking away and adding up. Squaring and square rooting if you are feeling really adventurous! Charts: Putting dots on a piece of graph paper! Exhausted, not! The equation of a straight line: y = ax+b. You can do it! Averages: Adding up and dividing. You know how to divide, don't you, Steve? Yes, it's mathematics, but nothing to frighten the horses! The book starts with a chapter with some history of AI. This is followed by a chapter of jargon, useful mathematics, and a description of the main techniques. Then it's one chapter on each of Nearest Neighbours, Regression, Clustering, Decision Trees, Neural Networks and Reinforcement Learning. Each of these in-depth chapters covers uses of the technique, the mathematical details, a real example and then a project for readers to work through on their own or in teams. The book ends with sources for some useful data.

Détails de l'édition

• Éditeur: Panda Ohana Publishing
• Date d'édition: 2023
• Langue: anglais
• ISBN 10: 1916081649
• ISBN 13: 9781916081642
• Reliure: Broché
• Nombre de pages: 99
• Coordonnées du fabricant: Printed by Amazon on behalf of the author; https://www.amazon.fr/hz/contact-us; ; c/o Amazon Media EU S.à.r.l., 38 Avenue John F. Kennedy; Luxembourg; L-1855; Luxembourg