- Chapter 1: Simple Linear Regression
- Chapter 2: Multiple Linear Regression
Supervised Learning from First Principles
This book is 5% completeLast updated on 2026-05-29
PLEASE NOTE THAT THIS IS NOT THE FULL BOOK BUT JUST CHAPTER 1 and 2 because a simple topic like Simple Linear Regression became 20+ pages long. As a full-time frontend architect, I'm writing and releasing this book chapter by chapter, at a pace that fits around my day job and life. So, think of this as a journey we're taking together, one concept at a time. REST OF THE CHAPTERS WILL BE AVAILABLE…
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This book is primarily written for software engineers, developers, and technical professionals from non-ML backgrounds who want meaningful exposure to Machine Learning but feel intimidated by the mathematics, jargon, or academic depth often associated with the field. Whether you are a student, a developer exploring a new domain, or a professional looking to understand how machines learn from data, this book aims to guide you step by step. If you are willing to think deeply, revisit concepts, and build your understanding from the ground up, you will find this book a useful companion on your journey.
The goal is not merely to teach APIs or frameworks, but to gradually build intuition from first principles so that you can understand how machines actually learn from data. The book assumes curiosity, patience, and a willingness to think deeply about concepts, but it does not assume prior expertise in Machine Learning, statistics, or advanced mathematics.
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