Introduction to Statistics, Machine Learning & AI (by Erwin Nijmeijer) is a practical, self-contained introduction that takes readers from the basics of statistics all the way to modern generative AI.This book originated from twenty pages the author wrote to help his daughter with an introduction to statistics, and has since grown into a comprehensive guide for students and professionals. The book is organized into clearly structured sections It's structured in progressive parts:1. Statistics — averages, spread, the normal distribution, sampling, comparing means, and ANOVA.2. Linear algebra — used as a toolkit for performing statistical calculations efficiently.3. Machine Learning — how systems learn patterns from data, illustrated with hands-on Python examples 4. Deep Learning — neural networks from first principles , built up to a TensorFlow/Keras example that trains a model to predict a tree's growth curve.5. Artificial Intelligence — how large language models like ChatGPT actually work: explained step by step and grounded in a simple Python-built language model.The author, a specialist with 25+ years in the high-tech industry, writes in an accessible, example-driven style aimed at readers who want to understand the mathematical foundations behind today's AI revolution — not just use the tools, but understand why they work.