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We're living through a transformation as profound as electricity or the printing press, yet AI often feels more like hype than help. With clear language, vivid illustrations, and humor, veteran AI researcher Sairam Sundaresan unpacks machine learning, natural language, computer vision, and recommender systems, showing how they drive the tech we use daily. You'll learn how AI works, where it appears, and how to make smarter choices about its role in your life and work. In two parts, the book moves from core concepts to real applications while debunking myths and stripping away buzzwords.
We're living through a transformation as profound as electricity or the printing press, yet AI often feels more like hype than help. With clear language, vivid illustrations, and humor, veteran AI researcher Sairam Sundaresan unpacks machine learning, natural language, computer vision, and recommender systems, showing how they drive the tech we use daily.
You'll learn how AI works, where it appears, and how to make smarter choices about its role in your life and work. In two parts, the book moves from core concepts to real applications while debunking myths and stripping away buzzwords.
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Autorenporträt
Sairam Sundaresan turns algorithms into stories and equations into doodles. He built AI at Qualcomm, Intel, and Valeo; authored patents and papers; mentored research at the Frontier Development Lab; and writes Gradiant Ascent, which is read by tens of thousands of readers who come for clarity and stay for the cartoons. He's still waiting for AI that gets his jokes.
Inhaltsangabe
Preface 1 - The AI Revolution 2 - The Fundamentals of AI 3 - A Few Good Algorithms 4 - Neural Networks 5 - AI That Reads and Writes 6 - Transformers and Large Language Models 7 - Machine Vision 8 - Generative Models 9 - AI That Recommends Stuff 10 - Building Intelligence Closing Thoughts Notes Index About the Author
Preface 1 - The AI Revolution 2 - The Fundamentals of AI 3 - A Few Good Algorithms 4 - Neural Networks 5 - AI That Reads and Writes 6 - Transformers and Large Language Models 7 - Machine Vision 8 - Generative Models 9 - AI That Recommends Stuff 10 - Building Intelligence Closing Thoughts Notes Index About the Author
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