Acknowledgements

This handbook grew, over many iterations, out of a simple conviction: that the path from first principles to the frontier of recommendation can be walked one hand-checkable step at a time.

My deepest gratitude goes first to my wife, who has stood quietly behind me through all of it — carrying our family so that I could give my full attention to this work. Whatever time and focus the book asked for, she made room for it. It exists because she did.

To my young son: you are my strongest motivation, and my surest one. Your laughter has a way of turning the longest day light, and you have kept me smiling and happy all the way through. This book is for you, too.

To my father and my mother, who gave me everything long before I could give anything back — a home, an education bought with their own sacrifice, and the love of learning that set me on this path together with the discipline to stay on it. Whatever is good in this work began with what they taught me, and I hope it makes them proud.

I am deeply indebted to my teachers and supervisors, Dr. Dang Quang Hieu and Assoc. Prof. Dr. Nguyen Duc Minh of the School of Electrical and Electronic Engineering, HUST, who guided me from my engineer’s thesis through my master’s and on to the doctorate. The years of patient mentorship they gave me are the foundation everything in these pages rests upon.

I owe a special debt to Dr. Dinh Anh Tuan — Co-founder and Chief Data Science Officer at Cogitativo (USA) — who has believed in me without fail, taught me, pushed me forward, and waited patiently for me to keep going when the road was slow. His generous, clear-sighted counsel has shaped how I think about research and about bringing artificial intelligence to bear in both academia and industry; this book is the better for it in more places than I can name.

Finally, to my students and colleagues at Minastik — many of them students of mine first, and colleagues since — who have stayed with me through the very first, hardest days of the company. You are dear to me, and you have mattered far beyond our research: in the real industry projects we have built together, with real clients and real data, your hands are in all of it. Thank you for keeping going alongside me through the hard days and the good ones. I am proud of you.

— Duong Tan Nghia

Tran Manh Hoang writes:

For my part, I want to thank the people who made my share of this book possible — and who made the long road toward it worth walking.

To my family, for the evenings and weekends this work quietly borrowed, and for the patient, unconditional love that asks for nothing while giving everything; nothing I do, these pages included, would be possible without you. To the teachers and mentors who shaped how I think — who taught me that a hard idea is not a wall but a door whose handle you simply have not found yet, and that the best thing a teacher can offer is not the answer but the patience to let a student reach it for themselves. And to the colleagues and collaborators whose questions, over many years, sharpened these ideas more than they know; the best of them never let a vague explanation pass, and the book is clearer for it.

A particular word about the friend whose name shares this cover. I have known Nghia for more than fifteen years, and I have had the rare privilege of watching a curious young engineer grow into a careful researcher and a builder who turns ideas into systems that work. Whatever encouragement I offered along the way, what he made of it was entirely his own — the courage to begin again from zero whenever the field demanded it, and the generosity to take his own hard-won understanding and shape it into something a complete beginner can actually use. That generosity is the spirit of this whole book, and helping it into the world has been one of the quiet joys of my career. To have walked a road this long beside a friend this good is a gift I do not take for granted.

And to you, the reader: we wrote this so that the path we once walked alone might be a little less lonely for you. Read it with a pen, check every number, and I hope that somewhere in these pages an idea clicks quietly into place — that small, bright oh, I see that kept both of us going.

— Tran Manh Hoang

A note on method: every worked example in this book was checked numerically before it was written down, and each figure plots the numbers of its own section. Any errors that remain are our own — corrections and suggestions from readers are warmly welcomed.

A note on the use of artificial intelligence (AI) tools: in preparing this book the authors used AI assistants (large language models) as a drafting, editing, and cross-checking aid — to help structure explanations, refine prose, and stress-test derivations. The authors directed all content and editorial decisions, independently verified every worked example numerically (as above), produced every figure from original source, and are solely responsible for the final text, including any errors. No AI system is an author of this work.