πŸ”” What’s New in the Book?
πŸ“… [Mar 25]: Major updates! Ch. 13 (ML Operations βš™οΈ), Ch. 17–19 (Sustainable AI 🌱, Robust AI πŸ›‘οΈ, and AI for Good 🌍).
πŸ“… [Mar 03]: New! Ch. 10 (AI Acceleration πŸš€) & Ch. 12 (Benchmarking AI πŸ“Š).
πŸ“… [Feb 02]: Updated Ch. 8 & 9 (AI Training πŸ‹οΈ & Efficient AI ⚑).
πŸ“… [Jan 16]: Expanded Ch. 1-7 + brand-new Ch. 4! πŸ”’πŸ› οΈ
πŸ—’οΈ More Updates: See the Full Changelog.

πŸš€ Shaping the Future: Every GitHub ⭐ helps empower learners and expand the global AI engineering community.
πŸ™ Support the Mission: Your ⭐ helps us keep this resource free, open, and improving for everyone.
✍️ Keep It Growing: A ⭐ a day keeps Vijay writing all day! β†’ Star the book on GitHub

Nicla Vision

These labs provide a unique opportunity to gain practical experience with machine learning (ML) systems. Unlike working with large models requiring data center-scale resources, these exercises allow you to directly interact with hardware and software using TinyML. This hands-on approach gives you a tangible understanding of the challenges and opportunities in deploying AI, albeit at a tiny scale. However, the principles are largely the same as what you would encounter when working with larger systems.

Nicla Vision. Source: Arduino

Nicla Vision. Source: Arduino

Pre-requisites

  • Nicla Vision Board: Ensure you have the Nicla Vision board.
  • USB Cable: For connecting the board to your computer.
  • Network: With internet access for downloading necessary software.

Setup

Exercises

Modality Task Description Link
Vision Image Classification Learn to classify images Link
Vision Object Detection Implement object detection Link
Sound Keyword Spotting Explore voice recognition systems Link
IMU Motion Classification and Anomaly Detection Classify motion data and detect anomalies Link