The Basics of AI Algorithms

Artificial Intelligence is transforming the modern world — but beneath the headlines about robots, automation, and smart machines lies something much simpler: the algorithm. These sets of rules, calculations, and logical steps are the beating heart of every intelligent system. In The Basics of AI Algorithms, Julian Vexley breaks down this vast and technical subject into ten clear, accessible chapters designed for the curious reader.

This audiobook explores how machines learn, adapt, and evolve through data. It starts with the core question — what exactly is an algorithm? — and then guides you through the major branches of machine learning: supervised learning, unsupervised learning, and reinforcement learning. From there, it examines the models that make AI work, including neural networks that mimic the brain, decision trees that provide clarity and structure, and ensemble methods that show the power of collaboration between multiple algorithms.

Each chapter reveals one of the essential pillars of artificial intelligence, explaining complex concepts in plain English without formulas or jargon. You’ll learn how Support Vector Machines find the best dividing line between data points, how K-Nearest Neighbours classify information by proximity, and how Gradient Descent helps machines improve themselves step by step — the same process that powers modern deep learning.

Throughout the audiobook, Vexley combines insight, historical context, and practical examples to show how algorithms shape the world around us — from search engines and medical diagnostics to voice recognition and autonomous vehicles. The writing is clear, engaging, and ideal for readers who want to understand AI without getting lost in mathematics or code.