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Grokking AI algorithms : how AI solves complex problems / Rishal Hurbans

By: Material type: TextPublication details: Shelter Island : Manning Publications, 2026Edition: 2nd edDescription: xxix, 558 pISBN:
  • 9781633434813
Subject(s): DDC classification:
  • 006.31 HUR-G
Summary: Artificial intelligence algorithms are the backbone of search and optimization, deep learning, reinforcement learning, and, of course, generative AI. This book introduces the most important AI algorithms using relatable illustrations, interesting examples, and thought-provoking exercises. Written in simple language and with lots of visual references and hands-on code examples, it helps you build a natural intuition into how intelligent systems learn, plan, and adapt. This second edition has been thoroughly revised, with new chapters on large language models, image generation, and more. You know you can solve a problem with AI--but how? Which algorithm do you pick and how do you properly implement it? This book makes it simple and easy to understand the most core and common AI approaches. You'll learn how to understand problem types, map real-world tasks to those problems, and how to design and implement the right algorithm--all following clear visual examples, pseudocode, and learning-oriented examples
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Artificial intelligence algorithms are the backbone of search and optimization, deep learning, reinforcement learning, and, of course, generative AI. This book introduces the most important AI algorithms using relatable illustrations, interesting examples, and thought-provoking exercises. Written in simple language and with lots of visual references and hands-on code examples, it helps you build a natural intuition into how intelligent systems learn, plan, and adapt. This second edition has been thoroughly revised, with new chapters on large language models, image generation, and more. You know you can solve a problem with AI--but how? Which algorithm do you pick and how do you properly implement it? This book makes it simple and easy to understand the most core and common AI approaches. You'll learn how to understand problem types, map real-world tasks to those problems, and how to design and implement the right algorithm--all following clear visual examples, pseudocode, and learning-oriented examples

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