This is the book I wish I had read when I started my career in Machine Learning.
Linear regression and gradient descent are the basis of all the AI models we use today. And yet, so few people truly understand these algorithms. As a Computer Science lecturer, these were the concepts my students struggled with the most. So I started looking for a book, a blog post, or anything that would explain them in a simple way. I could not find anything, so I wrote this book. Whether you are a student, a practitioner or just curious about AI, this book is a self-contained introduction. It is free of jargon and code. Just examples and simple ideas.