Grokking AI Algorithms: How AI solves complex problems, 2nd Edition

Artificial intelligence algorithms are the backbone of search and optimization, deep learning, reinforcement learning, and, of course, generative AI. Grokking AI Algorithms, Second Edition 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.

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

You know you can solve a problem with AI—but how? Which algorithm do you pick and how do you properly implement it? Grokking AI Algorithms, Second Edition 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.

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.