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Название: The Secrets of AI: a Math-Free Guide to Thinking Machines
Автор: Mukesh Borar
Издательство: Independently published
Год: 2023
Страниц: 117
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.19 MB
AI is undoubtedly the most critical technology that we must understand today. It is affecting everyone’s career, business and profession. However, AI is a complex and mysterious technology. To understand it, we have to climb a mountain of cryptic mathematical concepts and formulas, and success may still be elusive. ‘The Secrets of AI’ addresses this and explains AI in a simple, math-free language. This book sidesteps arcane algorithmic details and presents AI from the important perspectives of – intelligence, engineering, design, learnability, trust and business. It provides deep insights into the symbiotic relationships between data, learning and intelligence. The book has a strong focus on AI engineering. The AI development lifecycle is illustrated with an exhaustive case study on AI-driven live coverage of sports. It includes domain study, model architecture, feature engineering, model training, deployment and feedback learning. The book describes several design patterns and heuristics that are useful for building successful AI-powered systems.
Автор: Mukesh Borar
Издательство: Independently published
Год: 2023
Страниц: 117
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.19 MB
AI is undoubtedly the most critical technology that we must understand today. It is affecting everyone’s career, business and profession. However, AI is a complex and mysterious technology. To understand it, we have to climb a mountain of cryptic mathematical concepts and formulas, and success may still be elusive. ‘The Secrets of AI’ addresses this and explains AI in a simple, math-free language. This book sidesteps arcane algorithmic details and presents AI from the important perspectives of – intelligence, engineering, design, learnability, trust and business. It provides deep insights into the symbiotic relationships between data, learning and intelligence. The book has a strong focus on AI engineering. The AI development lifecycle is illustrated with an exhaustive case study on AI-driven live coverage of sports. It includes domain study, model architecture, feature engineering, model training, deployment and feedback learning. The book describes several design patterns and heuristics that are useful for building successful AI-powered systems.