cs249r_book/kits

Hardware Kits

Hands-on embedded ML labs for the MLSysBook

This directory contains hands-on embedded ML labs using Arduino, Raspberry Pi, and other microcontroller platforms.

Read Online | PDF

---

Platforms

Platform	Description
Arduino Nicla Vision	Compact AI camera board with STM32H7
Seeed XIAO ESP32S3	Tiny ESP32-S3 with camera support
Grove Vision AI V2	No-code AI vision module
Raspberry Pi	Full Linux SBC for edge AI

---

Quick Start

# Build HTML site
cd kits
ln -sf config/_quarto-html.yml _quarto.yml
quarto render

# Build PDF
ln -sf config/_quarto-pdf.yml _quarto.yml
quarto render --to titlepage-pdf

# Preview with live reload
quarto preview

---

Directory Structure

kits/
├── contents/                # Lab content
│   ├── arduino/             # Arduino Nicla Vision labs
│   ├── seeed/               # Seeed XIAO & Grove Vision labs
│   ├── raspi/               # Raspberry Pi labs
│   └── shared/              # Shared resources (DSP, features)
├── assets/                  # Images, styles, scripts
├── config/                  # Quarto configurations
│   ├── _quarto-html.yml     # Website config
│   └── _quarto-pdf.yml      # PDF config
├── tex/                     # LaTeX includes for PDF
├── filters/                 # Lua filters
└── index.qmd                # Landing page

---

Labs Overview

Each platform includes labs covering:

• Setup - Hardware setup and environment configuration
• Image Classification - CNN-based image recognition
• Object Detection - Real-time object detection
• Keyword Spotting - Audio wake word detection
• Motion Classification - IMU-based gesture recognition

---

Related

• MLSysBook - Main textbook
• TinyTorch - Build ML frameworks from scratch
• Website - Read labs online

---

Authors

• Marcelo Rovai - Primary author
• Vijay Janapa Reddi - Harvard University

---

License

Content is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

See LICENSE.md for details.