index.qmd

# Preface {.unnumbered}

Welcome to "Machine Learning Systems for TinyML" This book is your gateway to the fast-paced world of artificial intelligence within embedded systems. It as an extension of the foundational course, tinyML from CS249r at Harvard University.

Our aim? To make this book a collaborative effort that brings together insights from students, professionals, and the broader community. We want to create a one-stop guide that dives deep into the nuts and bolts of embedded AI and its many uses.

> "If you want to go fast, go alone. If you want to go far, go together."
> -- African Proverb

This isn't just a static textbook; it's a living, breathing document. We're making it open-source and continually updated to meet the ever-changing needs of this dynamic field. Expect a rich blend of expert knowledge that guides you through the complex interplay between cutting-edge algorithms and the foundational principles that make them work. We're setting the stage for the next big leap in tech innovation.

# Why We Wrote This Book

We're in an age where technology is always evolving. Open collaboration and sharing knowledge are the building blocks of true innovation. That's the spirit behind "Machine Learning Systems for TinyML." We're going beyond the traditional textbook model to create a living knowledge hub. 

The book covers principles, algorithms, and real-world application case studies, aiming to give you a deep understanding that will help you navigate the ever-changing landscape of embedded AI. By keeping it open, we're not just making learning accessible; we're inviting new ideas and ongoing improvements. In short, we're building a community where knowledge is free to grow and light the way forward in global embedded AI tech.

# What You'll Need to Know

Don't worry, you don't need to be a machine learning whiz to dive into this book. All you really need is a basic understanding of systems and a curiosity to explore how embedded hardware, AI, and software come together. This is where innovation happens, and a basic grasp of how systems work will be your compass.

We're also focusing on the exciting overlaps between these fields, aiming to create a learning environment where traditional boundaries fade away, making room for a more holistic, integrated view of modern tech. Your interest in embedded AI and low-level software will guide you through a rich and rewarding learning experience.

# Book Conventions

For details on the conventions used in this book, check out the [Conventions](./conventions.md) section.

# Want to Help Out?

If you're interested in contributing, you can find the guidelines [here](https://github.com/harvard-edge/cs249r_book).

# Get in Touch

Got questions or feedback? Feel free to [e-mail us](mailto:vj@eecs.harvard.edu?subject="CS249r%20TinyML%20Open%20Book").

# Contributors

A big thanks to everyone who's helped make this book what it is! You can see the full list of contributors [here](./contributors.qmd).