Grokking AI Algorithms, Second Edition

Rishal Hurbans

ISBN 10: 1633434818 / ISBN 13: 9781633434813

Editore: Manning Publications Jul 2026, 2026

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Neuware - Get a free Elektronisches Buch (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.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. In Grokking AI Algorithms, Second Edition you will discover: How to pick the right algorithm for each AI problem Learn the fundamentals of search (the foundation of modern AI) Building intelligent agents to solve puzzles Finding solutions using the theory of evolution and genetic algorithms Make predictions with neural networks Understand how AI gets better with reinforcement learning Building a LLM pipeline and image diffusion model from scratch About the technology AI algorithms are the backbone of search and optimization problems, deep learning, reinforcement learning, and, of course, generative AI. But knowing which algorithm to use and why is often harder than writing the code itself. Grokking AI Algorithms, Second Edition illuminates the algorithms behind modern generative AI with clear explanations, step-by-step code examples, and beautifully simple illustrations. About the book Everything you ll learn in this powerfully simple book is reinforced through engaging, end-to-end projects from solving mazes with search algorithms to navigating a car through a crowded parking lot with reinforcement learning. Plus, this second edition has been thoroughly revised with fresh chapters exploring the core algorithms of LLMs and image generation models. What's inside Search algorithms and swarm optimization Deep learning and neural networks Training AI with reinforcement learning Building a LLM pipeline for text generation About the reader Requires beginning to intermediate programming skills and high school level mathematics. No AI experience required. About the author Rishal Hurbans is an experienced technologist and serial entrepreneur specializing in AI engineering and human performance. Table of Contents 1 Intuition of AI 2 Search fundamentals 3 Intelligent search 4 Evolutionary algorithms 5 Advanced evolutionary approaches 6 Swarm intelligence: Ants 7 Swarm intelligence: Particles 8 Machine learning 9 Artificial neural networks 10 Reinforcement learning 11 Large language models 12 Generative image models.

Codice articolo 9781633434813

Dati bibliografici

• Titolo: Grokking AI Algorithms, Second Edition
• Editore: Manning Publications Jul 2026
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 1633434818
• ISBN 13: 9781633434813
• Rilegatura: Buch
• Edizione: seconda edizione
• Condizione: Neu
• Dimensioni: 234 L x 185 A x 46 P (millimetri) 234 millimetri di larghezza per 185 millimetri di altezza per 46 millimetri di profondità
• Peso: 771 grammi

Descrizione articolo

Riassunto

Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

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.

In Grokking AI Algorithms, Second Edition you will discover:

• How to pick the right algorithm for each AI problem
• Learn the fundamentals of search (the foundation of modern AI)
• Building intelligent agents to solve puzzles
• Finding solutions using the theory of evolution and genetic algorithms
• Make predictions with neural networks
• Understand how AI gets better with reinforcement learning
• Building a LLM pipeline and image diffusion model from scratch

About the technology

AI algorithms are the backbone of search and optimization problems, deep learning, reinforcement learning, and, of course, generative AI. But knowing which algorithm to use—and why—is often harder than writing the code itself. Grokking AI Algorithms, Second Edition illuminates the algorithms behind modern generative AI with clear explanations, step-by-step code examples, and beautifully simple illustrations.

About the book

Everything you’ll learn in this powerfully simple book is reinforced through engaging, end-to-end projects—from solving mazes with search algorithms to navigating a car through a crowded parking lot with reinforcement learning. Plus, this second edition has been thoroughly revised with fresh chapters exploring the core algorithms of LLMs and image generation models.

What's inside

• Search algorithms and swarm optimization
• Deep learning and neural networks
• Training AI with reinforcement learning
• Building a LLM pipeline for text generation

About the reader

Requires beginning to intermediate programming skills and high school level mathematics. No AI experience required.

About the author

Rishal Hurbans is an experienced technologist and serial entrepreneur specializing in AI engineering and human performance.

Table of Contents

1 Intuition of AI
2 Search fundamentals
3 Intelligent search
4 Evolutionary algorithms
5 Advanced evolutionary approaches
6 Swarm intelligence: Ants
7 Swarm intelligence: Particles
8 Machine learning
9 Artificial neural networks
10 Reinforcement learning
11 Large language models
12 Generative image models

Informazioni sull?autore

Rishal Hurbans is a technologist, founder, and international speaker.