How Machines Learn, Decide, and Create: A Common-Sense Guide to Artificial Intelligence

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Bol Artificial intelligence is no longer a distant vision. It is already changing how we work, learn, communicate, decide, and create. But what does AI actually do? How does it learn? Why can it be remarkably capable in one setting and surprisingly fragile in another? How Machines Learn, Decide, and Create offers a clear, approachable guide to the ideas behind modern artificial intelligence. Adrian Keller explains machine learning, neural networks, language models, multimodal systems, generative AI, agents, human-AI collaboration, bias, safety, and real-world deployment without requiring a computer-science background or math-heavy formulas. Through familiar examples, practical analogies, and concise illustrations, readers learn how machines find patterns in data, how models turn those patterns into predictions and actions, how generative systems produce language and images, how recommendation systems shape what we see, and why evaluation, robustness, responsibility, and alignment matter. Designed for curious readers, students, professionals, and anyone who wants a durable mental model of modern AI, this book replaces hype and mystery with a practical way to think clearly about what AI can do, where it fails, and how humans can use it responsibly.

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Artificial intelligence is no longer a distant vision. It is already changing how we work, learn, communicate, decide, and create. But what does AI actually do? How does it learn? Why can it be remarkably capable in one setting and surprisingly fragile in another? How Machines Learn, Decide, and Create offers a clear, approachable guide to the ideas behind modern artificial intelligence. Adrian Keller explains machine learning, neural networks, language models, multimodal systems, generative AI, agents, human-AI collaboration, bias, safety, and real-world deployment without requiring a computer-science background or math-heavy formulas. Through familiar examples, practical analogies, and concise illustrations, readers learn how machines find patterns in data, how models turn those patterns into predictions and actions, how generative systems produce language and images, how recommendation systems shape what we see, and why evaluation, robustness, responsibility, and alignment matter. Designed for curious readers, students, professionals, and anyone who wants a durable mental model of modern AI, this book replaces hype and mystery with a practical way to think clearly about what AI can do, where it fails, and how humans can use it responsibly.


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Merk Independently Published
EAN
  • 9798175702195
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